Triple
T18204983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BigBird |
E435879
|
entity |
| Predicate | availableIn |
P795
|
FINISHED |
| Object | Hugging Face Transformers library |
—
|
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 Transformers library | Statement: [BigBird, availableIn, Hugging Face Transformers library]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hugging Face Transformers library Context triple: [BigBird, availableIn, Hugging Face Transformers library]
-
A.
Hugging Face Transformers
chosen
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.
-
B.
Hugging Face
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.
-
C.
Hugging Face Tokenizers
Hugging Face Tokenizers is a fast, production-ready library for building and using modern text tokenization pipelines optimized for natural language processing and machine learning models.
-
D.
Hugging Face Accelerate
Hugging Face Accelerate is a lightweight library that simplifies running and scaling PyTorch and Transformers models across CPUs, GPUs, and distributed hardware with minimal code changes.
-
E.
TensorFlow Hub
TensorFlow Hub is a library and online repository of reusable machine learning models and components designed to simplify sharing and deploying pretrained models in TensorFlow applications.
- 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.