Triple
T15313190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AllenNLP research |
E366089
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | AllenNLP |
E366083
|
NE FINISHED |
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: AllenNLP | Statement: [AllenNLP research, relatedTo, AllenNLP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AllenNLP Context triple: [AllenNLP research, relatedTo, AllenNLP]
-
A.
AllenNLP
chosen
AllenNLP is an open-source natural language processing research library built on PyTorch, designed to facilitate the development and evaluation of state-of-the-art NLP models.
-
B.
AllenNLP research
AllenNLP research is a natural language processing research program focused on developing state-of-the-art models, tools, and methodologies for understanding and generating human language.
-
C.
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.
-
D.
BERT
BERT is a widely used transformer-based language model developed by Google that learns deep bidirectional representations of text for tasks like question answering and text classification.
-
E.
XLNet
XLNet is a generalized autoregressive pretraining model for natural language processing that improves on BERT by leveraging permutation-based language modeling to better capture bidirectional context.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03cd2d5a88190aead748920f93d47 |
completed | April 16, 2026, 1:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fef8a3da3881909b50cfbec0543adc |
completed | May 9, 2026, 9:04 a.m. |
Created at: April 10, 2026, 3:16 a.m.