GPT series
E106918
The GPT series is a family of large language models developed by OpenAI that generate human-like text and perform a wide range of natural language tasks.
All labels observed (2)
| Label | Occurrences |
|---|---|
| GPT series canonical | 7 |
| OpenAI GPT series | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T900538 — 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.
Target entity: GPT series Context triple: [GPT-4, modelFamily, GPT series]
-
A.
GPT-3
GPT-3 is a large-scale autoregressive language model known for generating human-like text and performing a wide range of natural language tasks with minimal fine-tuning.
-
B.
GPT-4
GPT-4 is a large multimodal language model known for its advanced reasoning, comprehension, and generation capabilities across text and images.
-
C.
ChatGPT
ChatGPT is an advanced conversational AI model developed by OpenAI that can understand and generate human-like text across a wide range of topics and tasks.
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D.
GPT-2
GPT-2 is a large transformer-based language model known for generating coherent, human-like text and sparking widespread discussion about the implications of advanced AI text generation.
-
E.
GPT-3.5
GPT-3.5 is a large language model that generates human-like text and powers conversational AI applications such as advanced chatbots and coding assistants.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: GPT series Target entity description: The GPT series is a family of large language models developed by OpenAI that generate human-like text and perform a wide range of natural language tasks.
-
A.
GPT-3
GPT-3 is a large-scale autoregressive language model known for generating human-like text and performing a wide range of natural language tasks with minimal fine-tuning.
-
B.
GPT-4
GPT-4 is a large multimodal language model known for its advanced reasoning, comprehension, and generation capabilities across text and images.
-
C.
ChatGPT
ChatGPT is an advanced conversational AI model developed by OpenAI that can understand and generate human-like text across a wide range of topics and tasks.
-
D.
GPT-2
GPT-2 is a large transformer-based language model known for generating coherent, human-like text and sparking widespread discussion about the implications of advanced AI text generation.
-
E.
GPT-3.5
GPT-3.5 is a large language model that generates human-like text and powers conversational AI applications such as advanced chatbots and coding assistants.
- F. None of above. chosen
Statements (51)
| Predicate | Object |
|---|---|
| instanceOf |
artificial intelligence model series
ⓘ
large language model ⓘ large language model ⓘ large language model ⓘ large language model ⓘ large language model family ⓘ large multimodal model ⓘ large multimodal model ⓘ |
| basedOn | transformer architecture ⓘ |
| capability |
few-shot learning
ⓘ
in-context learning ⓘ zero-shot learning ⓘ |
| creatorOrganizationType | AI research lab ⓘ |
| developer | OpenAI ⓘ |
| domain | natural language processing ⓘ |
| firstModelReleaseYear | 2018 ⓘ |
| hasMember |
ChatGPT
ⓘ
GPT-1 ⓘ GPT-2 ⓘ GPT-3 ⓘ GPT-3.5 ⓘ GPT-4 ⓘ GPT-4 ⓘ
surface form:
GPT-4 Turbo
GPT-4 ⓘ
surface form:
GPT-4.1
GPT-4.1-mini ⓘ GPT-4o ⓘ |
| language | English ⓘ |
| modelType | autoregressive language model ⓘ |
| partOf |
GPT series
self-linksurface differs
ⓘ
GPT series self-linksurface differs ⓘ GPT series self-linksurface differs ⓘ GPT series self-linksurface differs ⓘ GPT series self-linksurface differs ⓘ GPT series self-linksurface differs ⓘ |
| supportsLanguage | multilingual text ⓘ |
| task |
classification
ⓘ
code generation ⓘ conversation ⓘ information extraction ⓘ question answering ⓘ summarization ⓘ text completion ⓘ text generation ⓘ translation ⓘ |
| trainingDataType |
articles
ⓘ
books ⓘ code ⓘ internet text ⓘ |
| trainingObjective | next-token prediction ⓘ |
| uses |
deep learning
ⓘ
self-attention ⓘ |
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.
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.
Subject: GPT series Description of subject: The GPT series is a family of large language models developed by OpenAI that generate human-like text and perform a wide range of natural language tasks.
Referenced by (8)
Full triples — surface form annotated when it differs from this entity's canonical label.