Triple
T18204284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DistilBERT |
E435865
|
entity |
| Predicate | developedBy |
P73
|
FINISHED |
| Object | Hugging Face |
—
|
NE NERFINISHED |
How this triple was built (2 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: Hugging Face | Statement: [DistilBERT, developedBy, Hugging Face]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hugging Face Context triple: [DistilBERT, developedBy, Hugging Face]
-
A.
Hugging Face
chosen
Hugging Face is an AI company and open-source community best known for its tools and libraries that make it easy to build, share, and deploy state-of-the-art machine learning models.
-
B.
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.
-
C.
OpenAI
OpenAI is an artificial intelligence research organization best known for developing advanced AI models such as ChatGPT and GPT series.
-
D.
AI21 Labs
AI21 Labs is an artificial intelligence company specializing in large language models and advanced natural language processing technologies.
-
E.
EleutherAI
EleutherAI is an open-source research collective focused on developing and releasing large language models and related tools to advance accessible AI research.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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. |
Created at: April 10, 2026, 10:32 a.m.