openapi: 3.0.0
info:
title: Academic Graph API
version: '1.0'
description: "Fetch paper and author data from the Semantic Scholar Academic Graph\
\ (S2AG).\n
\n Some things to note:\n
\n \
\ - If you are using an API key, it must be set in the header
x-api-key\
\ (case-sensitive). \n - We have two different IDs for a single paper:\n\
\
\n paperId - string - The primary way\
\ to identify papers when using our website or this API \n corpusId\
\ - int64 - A second way to identify papers. Our datasets use corpusId when pointing\
\ to papers. \n
\n \n - Other useful resources
\n "
servers:
- url: https://api.semanticscholar.org/graph/v1
paths:
/author/batch:
post:
summary: Get details for multiple authors at once
operationId: post_graph_get_authors
tags:
- Author Data
description: "* Fields is a single-value string parameter, not a multi-value\
\ one.\n* It is a query parameter, not to be submitted in the POST request's\
\ body.\n\nIn python:\n\n r = requests.post(\n 'https://api.semanticscholar.org/graph/v1/author/batch',\n\
\ params={'fields': 'name,hIndex,citationCount'},\n json={\"\
ids\":[\"1741101\", \"1780531\"]}\n )\n print(json.dumps(r.json(), indent=2))\n\
\n [\n {\n \"authorId\": \"1741101\",\n \"name\": \"\
Oren Etzioni\",\n \"citationCount\": 34803,\n \"hIndex\": 86\n\
\ },\n {\n \"authorId\": \"1780531\",\n \"name\":\
\ \"Daniel S. Weld\",\n \"citationCount\": 35526,\n \"hIndex\"\
: 89\n }\n ]\n\nOther Examples:\n\n https://api.semanticscholar.org/graph/v1/author/batch \n\
\ \n {\"ids\":[\"1741101\", \"1780531\", \"48323507\"\
]} \n - Returns details for 3 authors.
\n - Each\
\ author returns the field authorId and name if no other fields are specified.
\n\
\
\n https://api.semanticscholar.org/graph/v1/author/batch?fields=url,name,paperCount,papers,papers.title,papers.openAccessPdf \n\
\ \n {\"ids\":[\"1741101\", \"1780531\", \"48323507\"\
]} \n - Returns authorID, url, name, paperCount, and list\
\ of papers for 3 authors.
\n - Each paper has its paperID, title,\
\ and link if available.
\n
\n
\n
\nLimitations:\n\n\
\ - Can only process 1,000 author ids at a time.
\n - Can only\
\ return up to 10 MB of data at a time.
\n
"
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/AuthorIdList'
responses:
'400':
description: Bad query parameters
content:
application/json:
schema:
$ref: '#/components/schemas/Error400'
'200':
description: List of authors with default or requested fields
content:
application/json:
schema:
$ref: '#/components/schemas/AuthorWithPapers'
/author/search:
get:
summary: Search for authors by name
operationId: get_graph_get_author_search
tags:
- Author Data
description: "Specifying papers fields in the request will return\
\ all papers linked to each author in the results. Set a limit\
\ on the search results to reduce output size and latency.
\nExamples:\n\
\n https://api.semanticscholar.org/graph/v1/author/search?query=adam+smith \n\
\ \n - Returns with total=490, offset=0, next=100, and data\
\ is a list of 100 authors.
\n - Each author has their authorId\
\ and name.
\n
\n https://api.semanticscholar.org/graph/v1/author/search?query=adam+smith&fields=name,url,papers.title,papers.year&limit=5 \n\
\ \n - Returns with total=490, offset=0, next=5, and data\
\ is a list of 5 authors.
\n - Each author has authorId, name,\
\ url, and a list of their papers title and year.
\n
\n https://api.semanticscholar.org/graph/v1/author/search?query=totalGarbageNonsense \n\
\ \n - Returns with total = 0, offset=0, and data is a list\
\ of 0 author.
\n
\n
\n Limitations:\n\n - Can\
\ only return up to 10 MB of data at a time.
\n
"
responses:
'400':
description: Bad query parameters
content:
application/json:
schema:
$ref: '#/components/schemas/Error400'
'200':
description: Batch of authors with default or requested fields
content:
application/json:
schema:
$ref: '#/components/schemas/AuthorSearchBatch'
/author/{author_id}:
get:
summary: Details about an author
operationId: get_graph_get_author
tags:
- Author Data
description: "Examples:\n\n https://api.semanticscholar.org/graph/v1/author/1741101 \n\
\ \n - Returns the author's authorId and name.
\n
\n\
\ https://api.semanticscholar.org/graph/v1/author/1741101?fields=url,papers \n\
\ \n - Returns the author's authorId, url, and list of papers.\
\
\n - Each paper has its paperId plus its title.
\n \
\
\n https://api.semanticscholar.org/graph/v1/author/1741101?fields=url,papers.abstract,papers.authors \n\
\ \n - Returns the author's authorId, url, and list of papers.\
\
\n - Each paper has its paperId, abstract, and list of authors.
\n\
\ - In that list of authors, each author has their authorId and name.
\n\
\
\n
\n Limitations:\n \n - Can only return\
\ up to 10 MB of data at a time.
\n
\n
"
responses:
'404':
description: Bad paper id
content:
application/json:
schema:
$ref: '#/components/schemas/Error404'
'400':
description: Bad query parameters
content:
application/json:
schema:
$ref: '#/components/schemas/Error400'
'200':
description: Author with default or requested fields
content:
application/json:
schema:
$ref: '#/components/schemas/AuthorWithPapers'
/author/{author_id}/papers:
get:
summary: Details about an author's papers
operationId: get_graph_get_author_papers
tags:
- Author Data
description: "Fetch the papers of an author in batches.
\nOnly retrieves\
\ the most recent 10,000 citations/references for papers belonging to the\
\ batch.
\nTo retrieve the full set of citations for a paper,\nuse the\
\ /paper/{paper_id}/citations endpoint\n
\nExamples:\n\n https://api.semanticscholar.org/graph/v1/author/1741101/papers \n\
\ \n - Return with offset=0, and data is a list of the first\
\ 100 papers.
\n - Each paper has its paperId and title.
\n\
\
\n https://api.semanticscholar.org/graph/v1/author/1741101/papers?fields=url,year,authors&limit=2 \n\
\ \n - Returns with offset=0, next=2, and data is a list of\
\ 2 papers.
\n - Each paper has its paperId, url, year, and list\
\ of authors.
\n - Each author has their authorId and name.
\n\
\
\n https://api.semanticscholar.org/graph/v1/author/1741101/papers?fields=citations.authors&offset=260 \n\
\ \n - Returns with offset=260, and data is a list of the\
\ last 4 papers.
\n - Each paper has its paperId and a list of\
\ citations.
\n - Each citation has its paperId and a list of\
\ authors.
\n - Each author has their authorId and name.
\n\
\
\n
"
responses:
'404':
description: Bad paper id
content:
application/json:
schema:
$ref: '#/components/schemas/Error404'
'400':
description: Bad query parameters
content:
application/json:
schema:
$ref: '#/components/schemas/Error400'
'200':
description: List of papers with default or requested fields
content:
application/json:
schema:
$ref: '#/components/schemas/AuthorPaperBatch'
/paper/autocomplete:
get:
summary: Suggest paper query completions
operationId: get_graph_get_paper_autocomplete
tags:
- Paper Data
description: 'To support interactive query-completion, return minimal information
about papers matching a partial query
Example:
https://api.semanticscholar.org/graph/v1/paper/autocomplete?query=semanti'
responses:
'400':
description: Bad query parameters
content:
application/json:
schema:
$ref: '#/components/schemas/Error400'
'200':
description: Batch of papers with default or requested fields
content:
application/json:
schema:
$ref: '#/components/schemas/PaperAutocomplete'
/paper/batch:
post:
summary: Get details for multiple papers at once
operationId: post_graph_get_papers
tags:
- Paper Data
description: "* Fields is a single-value string parameter, not a multi-value\
\ one.\n* It is a query parameter, not to be submitted in the POST request's\
\ body.\n\nIn python:\n\n r = requests.post(\n 'https://api.semanticscholar.org/graph/v1/paper/batch',\n\
\ params={'fields': 'referenceCount,citationCount,title'},\n \
\ json={\"ids\": [\"649def34f8be52c8b66281af98ae884c09aef38b\", \"ARXIV:2106.15928\"\
]}\n )\n print(json.dumps(r.json(), indent=2))\n\n [\n {\n \
\ \"paperId\": \"649def34f8be52c8b66281af98ae884c09aef38b\",\n \
\ \"title\": \"Construction of the Literature Graph in Semantic Scholar\"\
,\n \"referenceCount\": 27,\n \"citationCount\": 299\n \
\ },\n {\n \"paperId\": \"f712fab0d58ae6492e3cdfc1933dae103ec12d5d\"\
,\n \"title\": \"Reinfection and low cross-immunity as drivers of epidemic\
\ resurgence under high seroprevalence: a model-based approach with application\
\ to Amazonas, Brazil\",\n \"referenceCount\": 13,\n \"citationCount\"\
: 0\n }\n ]\n\nOther Examples:\n\n https://api.semanticscholar.org/graph/v1/paper/batch \n\
\ \n {\"ids\":[\"649def34f8be52c8b66281af98ae884c09aef38b\"\
, \"ARXIV:2106.15928\"]} \n - Returns details for 2 papers.
\n\
\ - Each paper has its paperId and title.
\n
\n \
\ https://api.semanticscholar.org/graph/v1/paper/batch?fields=title,isOpenAccess,openAccessPdf,authors \n\
\ \n {\"ids\":[\"649def34f8be52c8b66281af98ae884c09aef38b\"\
, \"ARXIV:2106.15928\"]} \n - Returns all requested info\
\ plus paper IDs for 2 papers.
\n
\n
\n
\nLimitations:\n\
\n - Can only process 500 paper ids at a time.
\n - Can\
\ only return up to 10 MB of data at a time.
\n - Can only return\
\ up to 9999 citations at a time.
\n - For a list of supported IDs\
\ reference the \"Details about a paper\" endpoint.
\n
"
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/PaperBatch'
responses:
'400':
description: Bad query parameters
content:
application/json:
schema:
$ref: '#/components/schemas/Error400'
'200':
description: List of papers with default or requested fields
content:
application/json:
schema:
$ref: '#/components/schemas/FullPaper'
/paper/search:
get:
summary: Paper relevance search
operationId: get_graph_paper_relevance_search
tags:
- Paper Data
description: "Examples:\n\n https://api.semanticscholar.org/graph/v1/paper/search?query=covid+vaccination&offset=100&limit=3 \n\
\ \n - Returns with total=576278, offset=100, next=103, and data\
\ is a list of 3 papers.
\n - Each paper has its paperId and title.\
\
\n
\n https://api.semanticscholar.org/graph/v1/paper/search?query=covid&fields=url,abstract,authors \n\
\ \n - Returns with total=639637, offset=0, next=100, and data is\
\ a list of 100 papers.
\n - Each paper has paperId, url, abstract,\
\ and a list of authors.
\n - Each author under that list has authorId\
\ and name.
\n
\n https://api.semanticscholar.org/graph/v1/paper/search?query=totalGarbageNonsense \n\
\ \n - Returns with total=0, offset=0, and data is a list of 0 papers.
\n\
\
\n https://api.semanticscholar.org/graph/v1/paper/search?query=covid&year=2020-2023&openAccessPdf&fieldsOfStudy=Physics,Philosophy&fields=title,year,authors \n\
\ \n - Returns with total=8471, offset=0, next=10, and data is a\
\ list of 10 papers.
\n - Filters to include only papers published\
\ between 2020-2023.
\n - Filters to include only papers with open\
\ access PDFs.
\n - Filters to include only papers that have a field\
\ of study either matching Physics or Philosophy.
\n - Each paper\
\ has the fields paperId, title, year, and authors.
\n
\n
\n\
\ Limitations:\n \n - Can only return up to 1,000 relevance-ranked\
\ results. For larger queries, see \"/search/bulk\" or the Datasets API.
\n\
\ - Can only return up to 10 MB of data at a time.
\n
\n\
"
responses:
'400':
description: Bad query parameters
content:
application/json:
schema:
$ref: '#/components/schemas/Error400'
'200':
description: Batch of papers with default or requested fields
content:
application/json:
schema:
$ref: '#/components/schemas/PaperRelevanceSearchBatch'
/paper/search/bulk:
get:
summary: Paper bulk search
operationId: get_graph_paper_bulk_search
tags:
- Paper Data
description: 'Behaves similarly to /paper/search, but is intended
for bulk retrieval of basic paper data without search relevance:
- Text query is optional and supports boolean logic for document matching.
- Papers can be filtered using various criteria.
- Up to 1,000 papers will be returned in each call.
- If there are more matching papers, a continuation "token" will be present.
- The query can be repeated with the token param added to efficiently continue
fetching matching papers.
Returns a structure with an estimated total matches, batch of matching papers,
and a continuation token if more results are available.
Limitations:
- Nested paper data, such as citations, references, etc, is not available
via this method.
- Up to 10,000,000 papers can be fetched via this method. For larger needs,
please use the Datasets API to retrieve full copies
of the corpus.
'
responses:
'400':
description: Bad query parameters
content:
application/json:
schema:
$ref: '#/components/schemas/Error400'
'200':
description: Batch of papers with default or requested fields
content:
application/json:
schema:
$ref: '#/components/schemas/PaperBulkSearchBatch'
/paper/search/match:
get:
summary: Paper title search
operationId: get_graph_paper_title_search
tags:
- Paper Data
description: "Behaves similarly to /paper/search, but is intended\
\ for retrieval of a single paper based on closest title match to given query.\n\
Examples:\n\n https://api.semanticscholar.org/graph/v1/paper/search/match?query=Construction\
\ of the Literature Graph in Semantic Scholar \n \n - Returns\
\ a single paper that is the closest title match.
\n - Each paper\
\ has its paperId, title, and matchScore as well as any other requested fields.
\n\
\
\n https://api.semanticscholar.org/graph/v1/paper/search/match?query=totalGarbageNonsense \n\
\ \n - Returns with a 404 error and a \"Title match not found\"\
\ message.
\n
\n
\n
\n Limitations:\n \n \
\ - Will only return the single highest match result.
\n
\n\
"
responses:
'404':
description: No title match
content:
application/json:
schema:
$ref: '#/components/schemas/Error404'
'400':
description: Bad query parameters
content:
application/json:
schema:
$ref: '#/components/schemas/Error400'
'200':
description: Best Title match paper with default or requested fields
content:
application/json:
schema:
$ref: '#/components/schemas/PaperMatch'
/paper/{paper_id}:
get:
summary: Details about a paper
operationId: get_graph_get_paper
tags:
- Paper Data
description: "Examples:\n\n https://api.semanticscholar.org/graph/v1/paper/649def34f8be52c8b66281af98ae884c09aef38b \n\
\ \n - Returns a paper with its paperId and title.
\n\
\
\n https://api.semanticscholar.org/graph/v1/paper/649def34f8be52c8b66281af98ae884c09aef38b?fields=url,year,authors \n\
\ \n - Returns the paper's paperId, url, year, and list of\
\ authors.
\n - Each author has authorId and name.
\n \
\
\n https://api.semanticscholar.org/graph/v1/paper/649def34f8be52c8b66281af98ae884c09aef38b?fields=citations.authors \n\
\ \n - Returns the paper's paperId and list of citations.\
\
\n - Each citation has its paperId plus its list of authors.
\n\
\ - Each author has their 2 always included fields of authorId and\
\ name.
\n
\n
\n Limitations:\n \n - Can\
\ only return up to 10 MB of data at a time.
\n
\n
"
responses:
'404':
description: Bad paper id
content:
application/json:
schema:
$ref: '#/components/schemas/Error404'
'400':
description: Bad query parameters
content:
application/json:
schema:
$ref: '#/components/schemas/Error400'
'200':
description: Paper with default or requested fields
content:
application/json:
schema:
$ref: '#/components/schemas/FullPaper'
/paper/{paper_id}/authors:
get:
summary: Details about a paper's authors
operationId: get_graph_get_paper_authors
tags:
- Paper Data
description: "Examples:\n\n https://api.semanticscholar.org/graph/v1/paper/649def34f8be52c8b66281af98ae884c09aef38b/authors \n\
\ \n - Returns with offset=0, and data is a list of all 3\
\ authors.
\n - Each author has their authorId and name
\n\
\
\n https://api.semanticscholar.org/graph/v1/paper/649def34f8be52c8b66281af98ae884c09aef38b/authors?fields=affiliations,papers&limit=2 \n\
\ \n - Returns with offset=0, next=2, and data is a list of\
\ 2 authors.
\n - Each author has their authorId, affiliations,\
\ and list of papers.
\n - Each paper has its paperId and title.
\n\
\
\n https://api.semanticscholar.org/graph/v1/paper/649def34f8be52c8b66281af98ae884c09aef38b/authors?fields=url,papers.year,papers.authors&offset=2 \n\
\ \n - Returns with offset=2, and data is a list containing\
\ the last author.
\n - This author has their authorId, url,\
\ and list of papers.
\n - Each paper has its paperId, year,\
\ and list of authors.
\n - In that list of authors, each author\
\ has their authorId and name.
\n
\n
"
responses:
'404':
description: Bad paper id
content:
application/json:
schema:
$ref: '#/components/schemas/Error404'
'400':
description: Bad query parameters
content:
application/json:
schema:
$ref: '#/components/schemas/Error400'
'200':
description: List of Authors with default or requested fields
content:
application/json:
schema:
$ref: '#/components/schemas/AuthorBatch'
/paper/{paper_id}/citations:
get:
summary: Details about a paper's citations
operationId: get_graph_get_paper_citations
tags:
- Paper Data
description: "Fetch details about the papers that cite this paper (i.e. papers\
\ in whose bibliography this paper appears)\n
\nExamples:\n\n \
\ - Let's suppose that the paper in the examples below has 1600 citations...
\n\
\ https://api.semanticscholar.org/graph/v1/paper/649def34f8be52c8b66281af98ae884c09aef38b/citations \n\
\ \n - Returns with offset=0, next=100, and data is a list\
\ of 100 citations.
\n - Each citation has a citingPaper which\
\ contains its paperId and title.
\n
\n https://api.semanticscholar.org/graph/v1/paper/649def34f8be52c8b66281af98ae884c09aef38b/citations?fields=contexts,intents,isInfluential,abstract&offset=200&limit=10 \n\
\ \n - Returns with offset=200, next=210, and data is a list\
\ of 10 citations.
\n - Each citation has contexts, intents,\
\ isInfluential, and a citingPaper which contains its paperId and abstract.
\n\
\
\n https://api.semanticscholar.org/graph/v1/paper/649def34f8be52c8b66281af98ae884c09aef38b/citations?fields=authors&offset=1500&limit=500 \n\
\ \n - Returns with offset=1500, and data is a list of the\
\ last 100 citations.
\n - Each citation has a citingPaper which\
\ contains its paperId plus a list of authors
\n - The authors\
\ under each citingPaper has their authorId and name.
\n
\n
"
responses:
'404':
description: Bad paper id
content:
application/json:
schema:
$ref: '#/components/schemas/Error404'
'400':
description: Bad query parameters
content:
application/json:
schema:
$ref: '#/components/schemas/Error400'
'200':
description: Batch of citations with default or requested fields
content:
application/json:
schema:
$ref: '#/components/schemas/CitationBatch'
/paper/{paper_id}/references:
get:
summary: Details about a paper's references
operationId: get_graph_get_paper_references
tags:
- Paper Data
description: "Fetch details about the papers cited by this paper (i.e. appearing\
\ in this paper's bibliography)\n
\nExamples:\n\n - Let's\
\ suppose that the paper in the examples below has 1600 references...
\n\
\ https://api.semanticscholar.org/graph/v1/paper/649def34f8be52c8b66281af98ae884c09aef38b/references \n\
\ \n - Returns with offset=0, next=100, and data is a list\
\ of 100 references.
\n - Each reference has a citedPaper which\
\ contains its paperId and title.
\n
\n https://api.semanticscholar.org/graph/v1/paper/649def34f8be52c8b66281af98ae884c09aef38b/references?fields=contexts,intents,isInfluential,abstract&offset=200&limit=10 \n\
\ \n - Returns with offset=200, next=210, and data is a list\
\ of 10 references.
\n - Each reference has contexts, intents,\
\ isInfluential, and a citedPaper which contains its paperId and abstract.
\n\
\
\n https://api.semanticscholar.org/graph/v1/paper/649def34f8be52c8b66281af98ae884c09aef38b/references?fields=authors&offset=1500&limit=500 \n\
\ \n - Returns with offset=1500, and data is a list of the\
\ last 100 references.
\n - Each reference has a citedPaper which\
\ contains its paperId plus a list of authors
\n - The authors\
\ under each citedPaper has their authorId and name.
\n
\n
"
responses:
'404':
description: Bad paper id
content:
application/json:
schema:
$ref: '#/components/schemas/Error404'
'400':
description: Bad query parameters
content:
application/json:
schema:
$ref: '#/components/schemas/Error400'
'200':
description: Batch of references with default or requested fields
content:
application/json:
schema:
$ref: '#/components/schemas/ReferenceBatch'
/snippet/search:
get:
summary: Text snippet search
operationId: get_snippet_search
tags:
- Snippet Text
description: "Return the text snippets that most closely match the query. Text\
\ snippets are excerpts of approximately 500 words, drawn from a paper's title,\
\ abstract, and body text, but excluding figure captions and the bibliography.\n\
It will return the highest ranked snippet first, as well as some basic data\
\ about the paper it was found in.\nExamples:\n\n https://api.semanticscholar.org/graph/v1/snippet/search?query=The\
\ literature graph is a property graph with directed edges&limit=1 \n\
\ \n - Returns a single snippet that is the highest ranked match.
\n\
\ - Each snippet has text, snippetKind, section, annotation data, and\
\ score. As well as the following data about the paper it comes from: corpusId,\
\ title, authors, and openAccessInfo.
\n
\n
\n
\n Limitations:\n\
\ \n - You must include a query.
\n - If you\
\ don't set a limit, it will automatically return 10 results.
\n \
\ - The max limit allowed is 1000.
\n
\n
"
responses:
'400':
description: Bad query parameters
content:
application/json:
schema:
$ref: '#/components/schemas/Error400'
'200':
description: Best snippet match with default fields
content:
application/json:
schema:
$ref: '#/components/schemas/SnippetMatch'
components:
schemas:
Error404:
properties:
error:
type: string
description: "Depending on the case, error message may be any of these:\n\
\n \"Paper/Author/Object not found\" \n \
\ \"Paper/Author/Object with id ### not found\" \n\
"
example: Requested object not found
type: object
Error400:
properties:
error:
type: string
description: "Depending on the case, error message may be any of these:\n\
\n \"Unrecognized or unsupported fields: [bad1, bad2,\
\ etc...]\" \n \"Unacceptable query params: [badK1=badV1,\
\ badK2=badV2, etc...}]\" \n \"Response would\
\ exceed maximum size....\" \n - This error will\
\ occur when the response exceeds 10 MB. Suggestions to either break the\
\ request into smaller batches, or make use of the limit and offset features\
\ will be presented.
\n - A custom message string
"
example: 'Unrecognized or unsupported fields: [author.creditCardNumber,
garbage]'
type: object
FullPaper:
properties:
paperId:
type: string
description: Semantic Scholar’s primary unique identifier for a paper.
example: 5c5751d45e298cea054f32b392c12c61027d2fe7
corpusId:
type: integer
description: Semantic Scholar’s secondary unique identifier for a paper.
example: 215416146
externalIds:
type: object
description: 'An object that contains the paper’s unique identifiers in
external sources. The external sources are limited to: ArXiv, MAG, ACL,
PubMed, Medline, PubMedCentral, DBLP, and DOI.'
example:
MAG: '3015453090'
DBLP: conf/acl/LoWNKW20
ACL: 2020.acl-main.447
DOI: 10.18653/V1/2020.ACL-MAIN.447
CorpusId: 215416146
url:
type: string
description: URL of the paper on the Semantic Scholar website.
example: https://www.semanticscholar.org/paper/5c5751d45e298cea054f32b392c12c61027d2fe7
title:
type: string
description: Title of the paper.
example: Construction of the Literature Graph in Semantic Scholar
abstract:
type: string
description: The paper's abstract. Note that due to legal reasons, this
may be missing even if we display an abstract on the website.
example: We describe a deployed scalable system for organizing published
scientific literature into a heterogeneous graph to facilitate algorithmic
manipulation and discovery.
venue:
type: string
description: The name of the paper’s publication venue.
example: Annual Meeting of the Association for Computational Linguistics
publicationVenue:
type: object
description: 'An object that contains the following information about the
journal or conference in which this paper was published: id (the venue’s
unique ID), name (the venue’s name), type (the type of venue), alternate_names
(an array of alternate names for the venue), and url (the venue’s website).'
example:
id: 1e33b3be-b2ab-46e9-96e8-d4eb4bad6e44
name: Annual Meeting of the Association for Computational Linguistics
type: conference
alternate_names:
- Annu Meet Assoc Comput Linguistics
- Meeting of the Association for Computational Linguistics
- ACL
- Meet Assoc Comput Linguistics
url: https://www.aclweb.org/anthology/venues/acl/
year:
type: integer
description: The year the paper was published.
example: 1997
referenceCount:
type: integer
description: The total number of papers this paper references.
example: 59
citationCount:
type: integer
description: The total number of papers that references this paper.
example: 453
influentialCitationCount:
type: integer
description: 'A subset of the citation count, where the cited publication
has a significant impact on the citing publication. Determined by Semantic
Scholar’s algorithm: https://www.semanticscholar.org/faq#influential-citations.'
example: 90
isOpenAccess:
type: boolean
description: 'Whether the paper is open access. More information here: https://www.openaccess.nl/en/what-is-open-access.'
example: true
openAccessPdf:
type: object
description: 'An object that contains the following parameters: url (a link
to the paper’s PDF), status (the type of open access https://en.wikipedia.org/wiki/Open_access#Colour_naming_system),
the paper''s license, and a legal disclaimer.'
example:
url: https://www.aclweb.org/anthology/2020.acl-main.447.pdf
status: HYBRID
license: CCBY
disclaimer: 'Notice: This snippet is extracted from the open access paper
or abstract available at https://aclanthology.org/2020.acl-main.447,
which is subject to the license by the author or copyright owner provided
with this content. Please go to the source to verify the license and
copyright information for your use.'
fieldsOfStudy:
type: array
description: 'A list of the paper’s high-level academic categories from
external sources. The possible fields are: Computer Science, Medicine,
Chemistry, Biology, Materials Science, Physics, Geology, Psychology, Art,
History, Geography, Sociology, Business, Political Science, Economics,
Philosophy, Mathematics, Engineering, Environmental Science, Agricultural
and Food Sciences, Education, Law, and Linguistics.'
example:
- Computer Science
items:
type: string
s2FieldsOfStudy:
type: array
description: 'An array of objects. Each object contains the following parameters:
category (a field of study. The possible fields are the same as in fieldsOfStudy),
and source (specifies whether the category was classified by Semantic
Scholar or by an external source. More information on how Semantic Scholar
classifies papers https://medium.com/ai2-blog/announcing-s2fos-an-open-source-academic-field-of-study-classifier-9d2f641949e5)'
example:
- category: Computer Science
source: external
- category: Computer Science
source: s2-fos-model
- category: Mathematics
source: s2-fos-model
items:
type: object
publicationTypes:
type: array
description: The type of this publication.
example:
- Journal Article
- Review
items:
type: string
publicationDate:
type: string
description: The date when this paper was published, in YYYY-MM-DD format.
example: '2024-04-29'
journal:
type: object
description: 'An object that contains the following parameters, if available:
name (the journal name), volume (the journal’s volume number), and pages
(the page number range)'
example:
volume: '40'
pages: 116 - 135
name: IETE Technical Review
citationStyles:
type: object
description: The BibTex bibliographical citation of the paper.
example:
bibtex: "@['JournalArticle', 'Conference']{Ammar2018ConstructionOT,\n\
\ author = {Waleed Ammar and Dirk Groeneveld and Chandra Bhagavatula\
\ and Iz Beltagy and Miles Crawford and Doug Downey and Jason Dunkelberger\
\ and Ahmed Elgohary and Sergey Feldman and Vu A. Ha and Rodney Michael\
\ Kinney and Sebastian Kohlmeier and Kyle Lo and Tyler C. Murray and\
\ Hsu-Han Ooi and Matthew E. Peters and Joanna L. Power and Sam Skjonsberg\
\ and Lucy Lu Wang and Christopher Wilhelm and Zheng Yuan and Madeleine\
\ van Zuylen and Oren Etzioni},\n booktitle = {NAACL},\n pages = {84-91},\n\
\ title = {Construction of the Literature Graph in Semantic Scholar},\n\
\ year = {2018}\n}\n"
authors:
type: array
items:
title: Author Info
allOf:
- $ref: '#/components/schemas/AuthorInPaper'
citations:
type: array
title: Paper Info
items:
$ref: '#/components/schemas/BasePaper'
references:
type: array
items:
title: Paper Info
allOf:
- $ref: '#/components/schemas/BasePaper'
embedding:
$ref: '#/components/schemas/Embedding'
tldr:
$ref: '#/components/schemas/Tldr'
textAvailability:
type: string
description: fulltext, abstract, or none, based on what we have available
for this paper
type: object
AuthorInPaper:
properties:
authorId:
type: string
title: This field will be provided if no fields are specified
description: Semantic Scholar’s unique ID for the author.
example: '1741101'
externalIds:
type: object
description: An object that contains the ORCID/DBLP IDs for the author,
if known.
example:
DBLP:
- 123
url:
type: string
description: URL of the author on the Semantic Scholar website.
example: https://www.semanticscholar.org/author/1741101
name:
type: string
title: This field will be provided if no fields are specified
description: Author’s name.
example: Oren Etzioni
affiliations:
type: array
description: Array of organizational affiliations for the author.
example:
- Allen Institute for AI
items:
type: string
homepage:
type: string
description: The author’s homepage.
example: https://allenai.org/
paperCount:
type: string
description: The author's total publications count.
example: 10
citationCount:
type: string
description: The author's total citations count.
example: 50
hIndex:
type: string
description: 'The author’s h-index, which is a measure of the productivity
and citation impact of the author’s publications: https://www.semanticscholar.org/faq#h-index'
example: 5
normalizedAffiliations:
type: array
description: Array of organizational ROR-based normalized affiliations for
the author (ROR - Research Organization Registry).
example:
- rorId: https://ror.org/05w520734
rorDisplayName: Allen Institute for Artificial Intelligence
items:
$ref: '#/components/schemas/NormalizedAffiliation'
type: object
NormalizedAffiliation:
properties:
rorId:
type: string
description: ROR (Research Organization Registry) unique ID.
example: https://ror.org/05w520734
rorDisplayName:
type: string
description: Official ROR display name.
example: Allen Institute for Artificial Intelligence
type: object
BasePaper:
properties:
paperId:
type: string
description: Semantic Scholar’s primary unique identifier for a paper.
example: 5c5751d45e298cea054f32b392c12c61027d2fe7
corpusId:
type: integer
description: Semantic Scholar’s secondary unique identifier for a paper.
example: 215416146
externalIds:
type: object
description: 'An object that contains the paper’s unique identifiers in
external sources. The external sources are limited to: ArXiv, MAG, ACL,
PubMed, Medline, PubMedCentral, DBLP, and DOI.'
example:
MAG: '3015453090'
DBLP: conf/acl/LoWNKW20
ACL: 2020.acl-main.447
DOI: 10.18653/V1/2020.ACL-MAIN.447
CorpusId: 215416146
url:
type: string
description: URL of the paper on the Semantic Scholar website.
example: https://www.semanticscholar.org/paper/5c5751d45e298cea054f32b392c12c61027d2fe7
title:
type: string
description: Title of the paper.
example: Construction of the Literature Graph in Semantic Scholar
abstract:
type: string
description: The paper's abstract. Note that due to legal reasons, this
may be missing even if we display an abstract on the website.
example: We describe a deployed scalable system for organizing published
scientific literature into a heterogeneous graph to facilitate algorithmic
manipulation and discovery.
venue:
type: string
description: The name of the paper’s publication venue.
example: Annual Meeting of the Association for Computational Linguistics
publicationVenue:
type: object
description: 'An object that contains the following information about the
journal or conference in which this paper was published: id (the venue’s
unique ID), name (the venue’s name), type (the type of venue), alternate_names
(an array of alternate names for the venue), and url (the venue’s website).'
example:
id: 1e33b3be-b2ab-46e9-96e8-d4eb4bad6e44
name: Annual Meeting of the Association for Computational Linguistics
type: conference
alternate_names:
- Annu Meet Assoc Comput Linguistics
- Meeting of the Association for Computational Linguistics
- ACL
- Meet Assoc Comput Linguistics
url: https://www.aclweb.org/anthology/venues/acl/
year:
type: integer
description: The year the paper was published.
example: 1997
referenceCount:
type: integer
description: The total number of papers this paper references.
example: 59
citationCount:
type: integer
description: The total number of papers that references this paper.
example: 453
influentialCitationCount:
type: integer
description: 'A subset of the citation count, where the cited publication
has a significant impact on the citing publication. Determined by Semantic
Scholar’s algorithm: https://www.semanticscholar.org/faq#influential-citations.'
example: 90
isOpenAccess:
type: boolean
description: 'Whether the paper is open access. More information here: https://www.openaccess.nl/en/what-is-open-access.'
example: true
openAccessPdf:
type: object
description: 'An object that contains the following parameters: url (a link
to the paper’s PDF), status (the type of open access https://en.wikipedia.org/wiki/Open_access#Colour_naming_system),
the paper''s license, and a legal disclaimer.'
example:
url: https://www.aclweb.org/anthology/2020.acl-main.447.pdf
status: HYBRID
license: CCBY
disclaimer: 'Notice: This snippet is extracted from the open access paper
or abstract available at https://aclanthology.org/2020.acl-main.447,
which is subject to the license by the author or copyright owner provided
with this content. Please go to the source to verify the license and
copyright information for your use.'
fieldsOfStudy:
type: array
description: 'A list of the paper’s high-level academic categories from
external sources. The possible fields are: Computer Science, Medicine,
Chemistry, Biology, Materials Science, Physics, Geology, Psychology, Art,
History, Geography, Sociology, Business, Political Science, Economics,
Philosophy, Mathematics, Engineering, Environmental Science, Agricultural
and Food Sciences, Education, Law, and Linguistics.'
example:
- Computer Science
items:
type: string
s2FieldsOfStudy:
type: array
description: 'An array of objects. Each object contains the following parameters:
category (a field of study. The possible fields are the same as in fieldsOfStudy),
and source (specifies whether the category was classified by Semantic
Scholar or by an external source. More information on how Semantic Scholar
classifies papers https://medium.com/ai2-blog/announcing-s2fos-an-open-source-academic-field-of-study-classifier-9d2f641949e5)'
example:
- category: Computer Science
source: external
- category: Computer Science
source: s2-fos-model
- category: Mathematics
source: s2-fos-model
items:
type: object
publicationTypes:
type: array
description: The type of this publication.
example:
- Journal Article
- Review
items:
type: string
publicationDate:
type: string
description: The date when this paper was published, in YYYY-MM-DD format.
example: '2024-04-29'
journal:
type: object
description: 'An object that contains the following parameters, if available:
name (the journal name), volume (the journal’s volume number), and pages
(the page number range)'
example:
volume: '40'
pages: 116 - 135
name: IETE Technical Review
citationStyles:
type: object
description: The BibTex bibliographical citation of the paper.
example:
bibtex: "@['JournalArticle', 'Conference']{Ammar2018ConstructionOT,\n\
\ author = {Waleed Ammar and Dirk Groeneveld and Chandra Bhagavatula\
\ and Iz Beltagy and Miles Crawford and Doug Downey and Jason Dunkelberger\
\ and Ahmed Elgohary and Sergey Feldman and Vu A. Ha and Rodney Michael\
\ Kinney and Sebastian Kohlmeier and Kyle Lo and Tyler C. Murray and\
\ Hsu-Han Ooi and Matthew E. Peters and Joanna L. Power and Sam Skjonsberg\
\ and Lucy Lu Wang and Christopher Wilhelm and Zheng Yuan and Madeleine\
\ van Zuylen and Oren Etzioni},\n booktitle = {NAACL},\n pages = {84-91},\n\
\ title = {Construction of the Literature Graph in Semantic Scholar},\n\
\ year = {2018}\n}\n"
authors:
type: array
title: Author Info
description: Details about the paper's authors
items:
$ref: '#/components/schemas/AuthorInfo'
type: object
AuthorInfo:
properties:
authorId:
type: string
title: This field will be provided if no fields are specified
description: Semantic Scholar’s unique ID for the author.
example: '1741101'
name:
type: string
title: This field will be provided if no fields are specified
description: Author’s name.
example: Oren Etzioni
type: object
Embedding:
properties:
model:
type: string
description: 'The Spector vector embedding model version: https://github.com/allenai/specter'
example: specter@v0.1.1
vector:
type: object
description: Numerical embedding vector.
example:
- -8.82082748413086
- -2.6610865592956543
type: object
Tldr:
properties:
model:
type: string
description: 'The tldr model version number: https://github.com/allenai/scitldr'
example: tldr@v2.0.0
text:
type: string
description: The tldr paper summary.
example: This paper reduces literature graph construction into familiar
NLP tasks, point out research challenges due to differences from standard
formulations of these tasks, and report empirical results for each task.
type: object
PaperBatch:
properties:
ids:
type: array
items:
type: string
example: 649def34f8be52c8b66281af98ae884c09aef38b
type: object
CitationBatch:
properties:
offset:
type: integer
description: Starting position for this batch.
next:
type: integer
description: Starting position of the next batch. Absent if no more data
exists.
data:
type: array
items:
title: contents of this batch
allOf:
- $ref: '#/components/schemas/Citation'
type: object
Citation:
properties:
contexts:
type: array
description: Array of text snippets where the reference to the paper is
mentioned.
example:
- SciBERT (Beltagy et al., 2019) follows the BERT’s masking strategy to
pre-train the model from scratch using a scientific corpus composed of
papers from Semantic Scholar (Ammar et al., 2018).
- 27M articles from the Semantic Scholar dataset (Ammar et al., 2018).
items:
type: string
intents:
type: array
description: 'Array of citation intents that summarizes how the reference
to the paper is mentioned. Possible intents: https://www.semanticscholar.org/faq#citation-intent'
example:
- methodology
items:
type: string
contextsWithIntent:
type: array
description: Array of objects that contain both contexts and the intents
they are associated with.
example:
- context: SciBERT (Beltagy et al., 2019) follows the BERT’s ...
intents:
- methodology
items:
type: object
isInfluential:
type: boolean
description: 'Whether the citing paper is highly influential. See more about
influential citations: https://www.semanticscholar.org/faq#influential-citations'
example: false
citingPaper:
description: Details about the citing paper
allOf:
- $ref: '#/components/schemas/BasePaper'
type: object
ReferenceBatch:
properties:
offset:
type: integer
description: Starting position for this batch.
next:
type: integer
description: Starting position of the next batch. Absent if no more data
exists.
data:
type: array
items:
title: contents of this batch
allOf:
- $ref: '#/components/schemas/Reference'
type: object
Reference:
properties:
contexts:
type: array
description: Array of text snippets where the reference to the paper is
mentioned.
example:
- SciBERT (Beltagy et al., 2019) follows the BERT’s masking strategy to
pre-train the model from scratch using a scientific corpus composed of
papers from Semantic Scholar (Ammar et al., 2018).
- 27M articles from the Semantic Scholar dataset (Ammar et al., 2018).
items:
type: string
intents:
type: array
description: 'Array of citation intents that summarizes how the reference
to the paper is mentioned. Possible intents: https://www.semanticscholar.org/faq#citation-intent'
example:
- methodology
items:
type: string
contextsWithIntent:
type: array
description: Array of objects that contain both contexts and the intents
they are associated with.
example:
- context: SciBERT (Beltagy et al., 2019) follows the BERT’s ...
intents:
- methodology
items:
type: object
isInfluential:
type: boolean
description: 'Whether the citing paper is highly influential. See more about
influential citations: https://www.semanticscholar.org/faq#influential-citations'
example: false
citedPaper:
description: Details about the cited paper
allOf:
- $ref: '#/components/schemas/BasePaper'
type: object
AuthorBatch:
properties:
offset:
type: integer
description: Starting position for this batch.
next:
type: integer
description: Starting position of the next batch. Absent if no more data
exists.
data:
type: array
items:
title: contents of this batch
allOf:
- $ref: '#/components/schemas/AuthorInPaperWithPapers'
type: object
AuthorInPaperWithPapers:
properties:
authorId:
type: string
title: This field will be provided if no fields are specified
description: Semantic Scholar’s unique ID for the author.
example: '1741101'
externalIds:
type: object
description: An object that contains the ORCID/DBLP IDs for the author,
if known.
example:
DBLP:
- 123
url:
type: string
description: URL of the author on the Semantic Scholar website.
example: https://www.semanticscholar.org/author/1741101
name:
type: string
title: This field will be provided if no fields are specified
description: Author’s name.
example: Oren Etzioni
affiliations:
type: array
description: Array of organizational affiliations for the author.
example:
- Allen Institute for AI
items:
type: string
homepage:
type: string
description: The author’s homepage.
example: https://allenai.org/
paperCount:
type: string
description: The author's total publications count.
example: 10
citationCount:
type: string
description: The author's total citations count.
example: 50
hIndex:
type: string
description: 'The author’s h-index, which is a measure of the productivity
and citation impact of the author’s publications: https://www.semanticscholar.org/faq#h-index'
example: 5
normalizedAffiliations:
type: array
description: Array of organizational ROR-based normalized affiliations for
the author (ROR - Research Organization Registry).
example:
- rorId: https://ror.org/05w520734
rorDisplayName: Allen Institute for Artificial Intelligence
items:
$ref: '#/components/schemas/NormalizedAffiliation'
papers:
type: array
items:
title: Paper Info
allOf:
- $ref: '#/components/schemas/BasePaper'
type: object
PaperRelevanceSearchBatch:
properties:
total:
type: string
description: 'Approximate number of matching search results.
Because of the subtleties of finding partial phrase matches in different
parts of the document, be cautious about interpreting the total field
as a count of documents containing any particular word in the query.'
example: 15117
offset:
type: integer
description: Starting position for this batch.
next:
type: integer
description: Starting position of the next batch. Absent if no more data
exists.
data:
type: array
items:
title: contents of this batch
allOf:
- $ref: '#/components/schemas/FullPaper'
type: object
PaperBulkSearchBatch:
properties:
total:
type: string
description: 'Approximate number of matching search results.
Because of the subtleties of finding partial phrase matches in different
parts of the document, be cautious about interpreting the total field
as a count of documents containing any particular word in the query.'
example: 15117
token:
type: string
description: A continuation token that must be provided to fetch the next
page of results. Present only when more results can be fetched.
example: SDKJFHSDKFHWIEFSFSGHEIURYC
data:
type: array
items:
title: Contents of this page
allOf:
- $ref: '#/components/schemas/FullPaper'
type: object
PaperMatch:
properties:
data:
type: array
items:
$ref: '#/components/schemas/Title Match Paper'
type: object
Title Match Paper:
properties:
matchScore:
type: integer
example: 174.2298
paperId:
type: string
description: Semantic Scholar’s primary unique identifier for a paper.
example: 5c5751d45e298cea054f32b392c12c61027d2fe7
corpusId:
type: integer
description: Semantic Scholar’s secondary unique identifier for a paper.
example: 215416146
externalIds:
type: object
description: 'An object that contains the paper’s unique identifiers in
external sources. The external sources are limited to: ArXiv, MAG, ACL,
PubMed, Medline, PubMedCentral, DBLP, and DOI.'
example:
MAG: '3015453090'
DBLP: conf/acl/LoWNKW20
ACL: 2020.acl-main.447
DOI: 10.18653/V1/2020.ACL-MAIN.447
CorpusId: 215416146
url:
type: string
description: URL of the paper on the Semantic Scholar website.
example: https://www.semanticscholar.org/paper/5c5751d45e298cea054f32b392c12c61027d2fe7
title:
type: string
description: Title of the paper.
example: Construction of the Literature Graph in Semantic Scholar
abstract:
type: string
description: The paper's abstract. Note that due to legal reasons, this
may be missing even if we display an abstract on the website.
example: We describe a deployed scalable system for organizing published
scientific literature into a heterogeneous graph to facilitate algorithmic
manipulation and discovery.
venue:
type: string
description: The name of the paper’s publication venue.
example: Annual Meeting of the Association for Computational Linguistics
publicationVenue:
type: object
description: 'An object that contains the following information about the
journal or conference in which this paper was published: id (the venue’s
unique ID), name (the venue’s name), type (the type of venue), alternate_names
(an array of alternate names for the venue), and url (the venue’s website).'
example:
id: 1e33b3be-b2ab-46e9-96e8-d4eb4bad6e44
name: Annual Meeting of the Association for Computational Linguistics
type: conference
alternate_names:
- Annu Meet Assoc Comput Linguistics
- Meeting of the Association for Computational Linguistics
- ACL
- Meet Assoc Comput Linguistics
url: https://www.aclweb.org/anthology/venues/acl/
year:
type: integer
description: The year the paper was published.
example: 1997
referenceCount:
type: integer
description: The total number of papers this paper references.
example: 59
citationCount:
type: integer
description: The total number of papers that references this paper.
example: 453
influentialCitationCount:
type: integer
description: 'A subset of the citation count, where the cited publication
has a significant impact on the citing publication. Determined by Semantic
Scholar’s algorithm: https://www.semanticscholar.org/faq#influential-citations.'
example: 90
isOpenAccess:
type: boolean
description: 'Whether the paper is open access. More information here: https://www.openaccess.nl/en/what-is-open-access.'
example: true
openAccessPdf:
type: object
description: 'An object that contains the following parameters: url (a link
to the paper’s PDF), status (the type of open access https://en.wikipedia.org/wiki/Open_access#Colour_naming_system),
the paper''s license, and a legal disclaimer.'
example:
url: https://www.aclweb.org/anthology/2020.acl-main.447.pdf
status: HYBRID
license: CCBY
disclaimer: 'Notice: This snippet is extracted from the open access paper
or abstract available at https://aclanthology.org/2020.acl-main.447,
which is subject to the license by the author or copyright owner provided
with this content. Please go to the source to verify the license and
copyright information for your use.'
fieldsOfStudy:
type: array
description: 'A list of the paper’s high-level academic categories from
external sources. The possible fields are: Computer Science, Medicine,
Chemistry, Biology, Materials Science, Physics, Geology, Psychology, Art,
History, Geography, Sociology, Business, Political Science, Economics,
Philosophy, Mathematics, Engineering, Environmental Science, Agricultural
and Food Sciences, Education, Law, and Linguistics.'
example:
- Computer Science
items:
type: string
s2FieldsOfStudy:
type: array
description: 'An array of objects. Each object contains the following parameters:
category (a field of study. The possible fields are the same as in fieldsOfStudy),
and source (specifies whether the category was classified by Semantic
Scholar or by an external source. More information on how Semantic Scholar
classifies papers https://medium.com/ai2-blog/announcing-s2fos-an-open-source-academic-field-of-study-classifier-9d2f641949e5)'
example:
- category: Computer Science
source: external
- category: Computer Science
source: s2-fos-model
- category: Mathematics
source: s2-fos-model
items:
type: object
publicationTypes:
type: array
description: The type of this publication.
example:
- Journal Article
- Review
items:
type: string
publicationDate:
type: string
description: The date when this paper was published, in YYYY-MM-DD format.
example: '2024-04-29'
journal:
type: object
description: 'An object that contains the following parameters, if available:
name (the journal name), volume (the journal’s volume number), and pages
(the page number range)'
example:
volume: '40'
pages: 116 - 135
name: IETE Technical Review
citationStyles:
type: object
description: The BibTex bibliographical citation of the paper.
example:
bibtex: "@['JournalArticle', 'Conference']{Ammar2018ConstructionOT,\n\
\ author = {Waleed Ammar and Dirk Groeneveld and Chandra Bhagavatula\
\ and Iz Beltagy and Miles Crawford and Doug Downey and Jason Dunkelberger\
\ and Ahmed Elgohary and Sergey Feldman and Vu A. Ha and Rodney Michael\
\ Kinney and Sebastian Kohlmeier and Kyle Lo and Tyler C. Murray and\
\ Hsu-Han Ooi and Matthew E. Peters and Joanna L. Power and Sam Skjonsberg\
\ and Lucy Lu Wang and Christopher Wilhelm and Zheng Yuan and Madeleine\
\ van Zuylen and Oren Etzioni},\n booktitle = {NAACL},\n pages = {84-91},\n\
\ title = {Construction of the Literature Graph in Semantic Scholar},\n\
\ year = {2018}\n}\n"
authors:
type: array
items:
title: Author Info
allOf:
- $ref: '#/components/schemas/AuthorInPaper'
citations:
type: array
title: Paper Info
items:
$ref: '#/components/schemas/BasePaper'
references:
type: array
items:
title: Paper Info
allOf:
- $ref: '#/components/schemas/BasePaper'
embedding:
$ref: '#/components/schemas/Embedding'
tldr:
$ref: '#/components/schemas/Tldr'
textAvailability:
type: string
description: fulltext, abstract, or none, based on what we have available
for this paper
type: object
PaperAutocomplete:
properties:
matches:
type: array
items:
$ref: '#/components/schemas/Autocomplete Paper'
type: object
Autocomplete Paper:
properties:
id:
type: string
description: The paper's primary unique identifier.
example: 649def34f8be52c8b66281af98ae884c09aef38b
title:
type: string
description: Title of the paper.
example: 'SciBERT: A Pretrained Language Model for Scientific Text'
authorsYear:
type: string
description: Summary of the authors of the paper and year of publication.
example: Beltagy et al., 2019
type: object
AuthorWithPapers:
properties:
authorId:
type: string
title: This field will be provided if no fields are specified
description: Semantic Scholar’s unique ID for the author.
example: '1741101'
externalIds:
type: object
description: An object that contains the ORCID/DBLP IDs for the author,
if known.
example:
DBLP:
- 123
url:
type: string
description: URL of the author on the Semantic Scholar website.
example: https://www.semanticscholar.org/author/1741101
name:
type: string
title: This field will be provided if no fields are specified
description: Author’s name.
example: Oren Etzioni
affiliations:
type: array
description: Array of organizational affiliations for the author.
example:
- Allen Institute for AI
items:
type: string
homepage:
type: string
description: The author’s homepage.
example: https://allenai.org/
paperCount:
type: string
description: The author's total publications count.
example: 10
citationCount:
type: string
description: The author's total citations count.
example: 50
hIndex:
type: string
description: 'The author’s h-index, which is a measure of the productivity
and citation impact of the author’s publications: https://www.semanticscholar.org/faq#h-index'
example: 5
papers:
type: array
items:
title: Paper Info
allOf:
- $ref: '#/components/schemas/BasePaper'
type: object
AuthorIdList:
properties:
ids:
type: array
items:
type: string
example: '1741101'
type: object
AuthorPaperBatch:
properties:
offset:
type: integer
description: Starting position for this batch.
next:
type: integer
description: Starting position of the next batch. Absent if no more data
exists.
data:
type: array
items:
title: contents of this batch
allOf:
- $ref: '#/components/schemas/PaperWithLinks'
type: object
PaperWithLinks:
properties:
paperId:
type: string
description: Semantic Scholar’s primary unique identifier for a paper.
example: 5c5751d45e298cea054f32b392c12c61027d2fe7
corpusId:
type: integer
description: Semantic Scholar’s secondary unique identifier for a paper.
example: 215416146
externalIds:
type: object
description: 'An object that contains the paper’s unique identifiers in
external sources. The external sources are limited to: ArXiv, MAG, ACL,
PubMed, Medline, PubMedCentral, DBLP, and DOI.'
example:
MAG: '3015453090'
DBLP: conf/acl/LoWNKW20
ACL: 2020.acl-main.447
DOI: 10.18653/V1/2020.ACL-MAIN.447
CorpusId: 215416146
url:
type: string
description: URL of the paper on the Semantic Scholar website.
example: https://www.semanticscholar.org/paper/5c5751d45e298cea054f32b392c12c61027d2fe7
title:
type: string
description: Title of the paper.
example: Construction of the Literature Graph in Semantic Scholar
abstract:
type: string
description: The paper's abstract. Note that due to legal reasons, this
may be missing even if we display an abstract on the website.
example: We describe a deployed scalable system for organizing published
scientific literature into a heterogeneous graph to facilitate algorithmic
manipulation and discovery.
venue:
type: string
description: The name of the paper’s publication venue.
example: Annual Meeting of the Association for Computational Linguistics
publicationVenue:
type: object
description: 'An object that contains the following information about the
journal or conference in which this paper was published: id (the venue’s
unique ID), name (the venue’s name), type (the type of venue), alternate_names
(an array of alternate names for the venue), and url (the venue’s website).'
example:
id: 1e33b3be-b2ab-46e9-96e8-d4eb4bad6e44
name: Annual Meeting of the Association for Computational Linguistics
type: conference
alternate_names:
- Annu Meet Assoc Comput Linguistics
- Meeting of the Association for Computational Linguistics
- ACL
- Meet Assoc Comput Linguistics
url: https://www.aclweb.org/anthology/venues/acl/
year:
type: integer
description: The year the paper was published.
example: 1997
referenceCount:
type: integer
description: The total number of papers this paper references.
example: 59
citationCount:
type: integer
description: The total number of papers that references this paper.
example: 453
influentialCitationCount:
type: integer
description: 'A subset of the citation count, where the cited publication
has a significant impact on the citing publication. Determined by Semantic
Scholar’s algorithm: https://www.semanticscholar.org/faq#influential-citations.'
example: 90
isOpenAccess:
type: boolean
description: 'Whether the paper is open access. More information here: https://www.openaccess.nl/en/what-is-open-access.'
example: true
openAccessPdf:
type: object
description: 'An object that contains the following parameters: url (a link
to the paper’s PDF), status (the type of open access https://en.wikipedia.org/wiki/Open_access#Colour_naming_system),
the paper''s license, and a legal disclaimer.'
example:
url: https://www.aclweb.org/anthology/2020.acl-main.447.pdf
status: HYBRID
license: CCBY
disclaimer: 'Notice: This snippet is extracted from the open access paper
or abstract available at https://aclanthology.org/2020.acl-main.447,
which is subject to the license by the author or copyright owner provided
with this content. Please go to the source to verify the license and
copyright information for your use.'
fieldsOfStudy:
type: array
description: 'A list of the paper’s high-level academic categories from
external sources. The possible fields are: Computer Science, Medicine,
Chemistry, Biology, Materials Science, Physics, Geology, Psychology, Art,
History, Geography, Sociology, Business, Political Science, Economics,
Philosophy, Mathematics, Engineering, Environmental Science, Agricultural
and Food Sciences, Education, Law, and Linguistics.'
example:
- Computer Science
items:
type: string
s2FieldsOfStudy:
type: array
description: 'An array of objects. Each object contains the following parameters:
category (a field of study. The possible fields are the same as in fieldsOfStudy),
and source (specifies whether the category was classified by Semantic
Scholar or by an external source. More information on how Semantic Scholar
classifies papers https://medium.com/ai2-blog/announcing-s2fos-an-open-source-academic-field-of-study-classifier-9d2f641949e5)'
example:
- category: Computer Science
source: external
- category: Computer Science
source: s2-fos-model
- category: Mathematics
source: s2-fos-model
items:
type: object
publicationTypes:
type: array
description: The type of this publication.
example:
- Journal Article
- Review
items:
type: string
publicationDate:
type: string
description: The date when this paper was published, in YYYY-MM-DD format.
example: '2024-04-29'
journal:
type: object
description: 'An object that contains the following parameters, if available:
name (the journal name), volume (the journal’s volume number), and pages
(the page number range)'
example:
volume: '40'
pages: 116 - 135
name: IETE Technical Review
citationStyles:
type: object
description: The BibTex bibliographical citation of the paper.
example:
bibtex: "@['JournalArticle', 'Conference']{Ammar2018ConstructionOT,\n\
\ author = {Waleed Ammar and Dirk Groeneveld and Chandra Bhagavatula\
\ and Iz Beltagy and Miles Crawford and Doug Downey and Jason Dunkelberger\
\ and Ahmed Elgohary and Sergey Feldman and Vu A. Ha and Rodney Michael\
\ Kinney and Sebastian Kohlmeier and Kyle Lo and Tyler C. Murray and\
\ Hsu-Han Ooi and Matthew E. Peters and Joanna L. Power and Sam Skjonsberg\
\ and Lucy Lu Wang and Christopher Wilhelm and Zheng Yuan and Madeleine\
\ van Zuylen and Oren Etzioni},\n booktitle = {NAACL},\n pages = {84-91},\n\
\ title = {Construction of the Literature Graph in Semantic Scholar},\n\
\ year = {2018}\n}\n"
authors:
type: array
title: Author Info
description: Details about the paper's authors
items:
$ref: '#/components/schemas/AuthorInfo'
citations:
type: array
title: Paper Info
items:
$ref: '#/components/schemas/PaperInfo'
references:
type: array
items:
title: Paper Info
allOf:
- $ref: '#/components/schemas/PaperInfo'
type: object
PaperInfo:
properties:
paperId:
type: string
description: Semantic Scholar’s primary unique identifier for a paper.
example: 5c5751d45e298cea054f32b392c12c61027d2fe7
corpusId:
type: integer
description: Semantic Scholar’s secondary unique identifier for a paper.
example: 215416146
url:
type: string
description: URL of the paper on the Semantic Scholar website.
example: https://www.semanticscholar.org/paper/5c5751d45e298cea054f32b392c12c61027d2fe7
title:
type: string
description: Title of the paper.
example: Construction of the Literature Graph in Semantic Scholar
venue:
type: string
description: The name of the paper’s publication venue.
example: Annual Meeting of the Association for Computational Linguistics
publicationVenue:
type: object
description: 'An object that contains the following information about the
journal or conference in which this paper was published: id (the venue’s
unique ID), name (the venue’s name), type (the type of venue), alternate_names
(an array of alternate names for the venue), and url (the venue’s website).'
example:
id: 1e33b3be-b2ab-46e9-96e8-d4eb4bad6e44
name: Annual Meeting of the Association for Computational Linguistics
type: conference
alternate_names:
- Annu Meet Assoc Comput Linguistics
- Meeting of the Association for Computational Linguistics
- ACL
- Meet Assoc Comput Linguistics
url: https://www.aclweb.org/anthology/venues/acl/
year:
type: integer
description: The year the paper was published.
example: 1997
authors:
type: array
title: Author Info
description: Details about the paper's authors
items:
$ref: '#/components/schemas/AuthorInfo'
type: object
AuthorSearchBatch:
properties:
total:
type: string
description: 'Approximate number of matching search results.
Because of the subtleties of finding partial phrase matches in different
parts of the document, be cautious about interpreting the total field
as a count of documents containing any particular word in the query.'
example: 15117
offset:
type: integer
description: Starting position for this batch.
next:
type: integer
description: Starting position of the next batch. Absent if no more data
exists.
data:
type: array
items:
title: contents of this batch
allOf:
- $ref: '#/components/schemas/AuthorWithPapers'
type: object
SnippetMatch:
properties:
data:
type: array
items:
$ref: '#/components/schemas/Snippet Match'
retrievalVersion:
type: string
description: A rough representation of the retrieval approach we've used
to get the results. We'll usually bump this if we change something about
how we get results. Note that the same retrievalVersion value doesn't
guarantee that you'll get the same results for the same query at different
times, and a different retrievalVersion value doesn't always mean you'll
get different results.
type: object
Snippet Match:
properties:
snippet:
$ref: '#/components/schemas/snippet'
score:
type: number
example: 0.561970777028496
paper:
$ref: '#/components/schemas/paper'
type: object
snippet:
properties:
text:
type: string
description: The direct quote or snippet from the paper relevant to the
query.
example: "In this paper, we discuss the construction of a graph, providing\
\ a symbolic representation of the scientific literature. We describe\
\ deployed models for identifying authors, references and entities in\
\ the paper text, and provide experimental results to evaluate the performance\
\ of each model. \n\nThree research directions follow from this work and\
\ other similar projects, e.g., Hahn-Powell et al. (2017); Wu et al. (2014):\
\ i) improving quality and enriching content of the literature graph (e.g.,\
\ ontology matching and knowledge base population). ii) aggregating domain-specific\
\ extractions across many papers to enable a better understanding of the\
\ literature as a whole (e.g., identifying demographic biases in clinical\
\ trial participants and summarizing empirical results on important tasks).\
\ iii) exploring the literature via natural language interfaces. \n\n\
In order to help future research efforts, we make the following resources\
\ publicly available: metadata for over 20 million papers,10 meaningful\
\ citations dataset,11 models for figure and table extraction,12 models\
\ for predicting citations in a paper draft 13 and models for extracting\
\ paper metadata,14 among other resources."
snippetKind:
type: string
description: 'Where the snippet is located, options are: title, abstract,
or body. '
example: body
section:
type: string
description: Only applies to snippets from the body, refers to the section
of the paper where the snippet is located.
example: Conclusion and Future Work
snippetOffset:
type: object
description: The location of the snippet within the paper.
example:
start: 24506
end: 25694
annotations:
$ref: '#/components/schemas/annotations'
type: object
annotations:
properties:
sentences:
type: array
items:
$ref: '#/components/schemas/sentence'
refMentions:
type: array
items:
$ref: '#/components/schemas/refMention'
type: object
sentence:
properties:
start:
type: integer
example: 0
end:
type: integer
example: 120
type: object
refMention:
properties:
start:
type: integer
example: 377
end:
type: integer
example: 402
matchedPaperCorpusId:
type: string
example: '7377848'
type: object
paper:
properties:
corpusId:
type: string
description: Semantic Scholar’s secondary unique identifier for a paper.
example: '19170988'
title:
type: string
description: Title of the paper.
example: Construction of the Literature Graph in Semantic Scholar
authors:
type: array
items:
type: string
description: Authors of the paper.
example:
- Bridger Waleed Ammar
- Dirk Groeneveld
- Chandra Bhagavatula
- Iz Beltagy
- Miles Crawford
- Doug Downey
- Jason Dunkelberger
- Ahmed Elgohary
- Sergey Feldman
- Vu A. Ha
- Rodney Michael Kinney
- Sebastian Kohlmeier
- Kyle Lo
- Tyler C. Murray
- Hsu-Han Ooi
- Matthew E. Peters
- Joanna L. Power
- Sam Skjonsberg
- Lucy Lu Wang
- Christopher Wilhelm
- Zheng Yuan
- Madeleine van Zuylen
- Oren Etzioni
openAccessInfo:
$ref: '#/components/schemas/openAccessInfo'
type: object
openAccessInfo:
properties:
license:
type: string
description: The license attached to the paper.
example: CCBY
status:
type: string
description: Paper's status (the type of open access https://en.wikipedia.org/wiki/Open_access#Colour_naming_system)
example: HYBRID
disclaimer:
type: string
description: A disclaimer about the open access use of this paper.
example: 'Notice: This snippet is extracted from the open access paper or
abstract available at https://arxiv.org/abs/1805.02262, which is subject
to the license by the author or copyright owner provided with this content.
Please go to the source to verify the license and copyright information
for your use.'
type: object
securitySchemes: {}