Triple
T18205267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VisionEncoderDecoderModel |
E435885
|
entity |
| Predicate | supportsDecoderModel |
P38601
|
FINISHED |
| Object | GPT2LMHeadModel |
—
|
NE NERFINISHED |
How this triple was built (3 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: GPT2LMHeadModel | Statement: [VisionEncoderDecoderModel, supportsDecoderModel, GPT2LMHeadModel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GPT2LMHeadModel Context triple: [VisionEncoderDecoderModel, supportsDecoderModel, GPT2LMHeadModel]
-
A.
GPT-2
chosen
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.
-
B.
Megatron-LM
Megatron-LM is a large-scale language model training framework developed by NVIDIA, designed to efficiently train massive transformer models through model, tensor, and pipeline parallelism.
-
C.
GPT-Neo
GPT-Neo is an open-source family of autoregressive language models developed by EleutherAI as a free alternative to OpenAI’s GPT-3.
-
D.
Hugging Face Transformers
Hugging Face Transformers is a widely used open-source library that provides state-of-the-art transformer-based models and tools for natural language processing and related machine learning tasks.
-
E.
LLaMA
LLaMA is a family of large language models developed by Meta AI, designed for efficient training and inference across a range of natural language processing tasks.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsDecoderModel Context triple: [VisionEncoderDecoderModel, supportsDecoderModel, GPT2LMHeadModel]
-
A.
supportsModelType
Indicates that an entity is compatible with, or can operate using, a specified model type.
-
B.
supportsModelVariant
chosen
Indicates that one entity is capable of operating with, being compatible with, or otherwise accommodating a specific variant of a model.
-
C.
supportsModelingOf
Indicates that one entity provides the capability or functionality needed to represent, simulate, or model another entity or process.
-
D.
supportsModelFamily
Indicates that one entity provides compatibility, functionality, or resources necessary for the operation or use of a particular model family.
-
E.
supportsAccessModel
Indicates that one entity enables, permits, or is compatible with a particular access model used by another entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e222831081908f7d5500424e3acb |
completed | April 19, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69e4332155d88190b106d0dceb4554af |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:32 a.m.