NAACL 2018
E771679
NAACL 2018 was a major computational linguistics conference where the influential ELMo deep contextualized word representation model was introduced.
All labels observed (6)
How this entity was disambiguated
This entity first appeared as the object of triple T8993081 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NAACL 2018 Context triple: [Elmo, publishedAtConference, NAACL 2018]
-
A.
EMNLP
EMNLP (Empirical Methods in Natural Language Processing) is a leading annual conference in computational linguistics and natural language processing research.
-
B.
ACM Transactions on Asian and Low-Resource Language Information Processing
ACM Transactions on Asian and Low-Resource Language Information Processing is a peer-reviewed scholarly journal focusing on computational linguistics, natural language processing, and information processing for Asian and other low-resource languages.
-
C.
NeurIPS
NeurIPS is a premier international conference focused on advances in machine learning, artificial intelligence, and computational neuroscience.
-
D.
TACL
TACL (Transactions of the Association for Computational Linguistics) is a leading peer-reviewed journal publishing high-quality research in natural language processing and computational linguistics.
-
E.
“A Computer Program for Understanding Natural Language”
“A Computer Program for Understanding Natural Language” is a landmark 1968 paper by Terry Winograd that presents an early natural language understanding system capable of interpreting and executing commands in a simulated blocks world.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: NAACL 2018 Target entity description: NAACL 2018 was a major computational linguistics conference where the influential ELMo deep contextualized word representation model was introduced.
-
A.
EMNLP
EMNLP (Empirical Methods in Natural Language Processing) is a leading annual conference in computational linguistics and natural language processing research.
-
B.
ACM Transactions on Asian and Low-Resource Language Information Processing
ACM Transactions on Asian and Low-Resource Language Information Processing is a peer-reviewed scholarly journal focusing on computational linguistics, natural language processing, and information processing for Asian and other low-resource languages.
-
C.
NeurIPS
NeurIPS is a premier international conference focused on advances in machine learning, artificial intelligence, and computational neuroscience.
-
D.
TACL
TACL (Transactions of the Association for Computational Linguistics) is a leading peer-reviewed journal publishing high-quality research in natural language processing and computational linguistics.
-
E.
“A Computer Program for Understanding Natural Language”
“A Computer Program for Understanding Natural Language” is a landmark 1968 paper by Terry Winograd that presents an early natural language understanding system capable of interpreting and executing commands in a simulated blocks world.
- F. None of above. chosen
Statements (46)
| Predicate | Object |
|---|---|
| instanceOf |
computational linguistics conference
ⓘ
scientific conference ⓘ |
| associatedWith | ELMo deep contextualized word representation model ⓘ |
| city | New Orleans ⓘ |
| country |
United States
ⓘ
linked to:
United States of America
|
| endDate | 2018-06-06 ⓘ |
| field |
computational linguistics
ⓘ
natural language processing ⓘ |
| focus | human language technologies ⓘ |
| hasAbbreviation |
NAACL-HLT 2018
ⓘ
linked to:
NAACL 2018
|
| hasEvent |
main conference
ⓘ
tutorials ⓘ workshops ⓘ |
| hasProceedings |
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
ⓘ
linked to:
NAACL 2018
|
| impact |
influenced subsequent contextual language models
ⓘ
popularized deep contextual word embeddings ⓘ |
| introducedModel |
ELMo
ⓘ
linked to:
Deep contextualized word representations
|
| language | English ⓘ |
| location | New Orleans, Louisiana, United States ⓘ |
| notablePaper | Deep contextualized word representations ⓘ |
| organizedBy |
North American Chapter of the Association for Computational Linguistics
ⓘ
linked to:
Association for Computational Linguistics
|
| paperAuthors |
Christopher Clark
ⓘ
Kenton Lee ⓘ Luke Zettlemoyer ⓘ Mark Neumann ⓘ Matt Gardner ⓘ Matthew E. Peters ⓘ Mohit Iyyer ⓘ |
| paperTitle | Deep contextualized word representations ⓘ |
| partOfSeries |
NAACL
ⓘ
linked to:
NAACL 2018
|
| publisherOfProceedings | Association for Computational Linguistics ⓘ |
| regionFocus | North America ⓘ |
| seriesNumber | 2018 edition ⓘ |
| startDate | 2018-06-01 ⓘ |
| submissionType | peer-reviewed papers ⓘ |
| topic |
dialogue systems
ⓘ
information extraction ⓘ language modeling ⓘ machine translation ⓘ question answering ⓘ semantic parsing ⓘ sentiment analysis ⓘ speech and language processing ⓘ syntactic parsing ⓘ text classification ⓘ |
| year | 2018 ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: NAACL 2018 Description of subject: NAACL 2018 was a major computational linguistics conference where the influential ELMo deep contextualized word representation model was introduced.
Referenced by (9)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: NAACL 2018
Deep contextualized word representations
→
publishedAt
→
2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
ⓘ
linked to: NAACL 2018
linked to: NAACL 2018
linked to: NAACL 2018
linked to: NAACL 2018
NAACL 2018
→
hasProceedings
→
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
ⓘ
linked to: NAACL 2018