Triple
T8729762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NLAW |
E207221
|
entity |
| Predicate | trainingVariant |
P44346
|
FINISHED |
| Object | NLAW training system |
—
|
LITERAL 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: NLAW training system | Statement: [NLAW, trainingVariant, NLAW training system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainingVariant Context triple: [NLAW, trainingVariant, NLAW training system]
-
A.
trainerVariant
Indicates a relationship where one trainer is an alternative or modified version of another trainer.
-
B.
trainingVersion
chosen
Indicates that one entity is a specific training iteration, release, or configuration derived from or associated with another entity.
-
C.
trainingUse
Indicates that something is used for training purposes, such as preparing, educating, or improving the skills or performance of an entity.
-
D.
trainingParadigm
Indicates the specific methodological framework or approach used to train an entity (such as a model, system, or agent).
-
E.
trainerModel
Indicates that one entity serves as the trainer or training source for a model 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_69ca8358e4008190898471a59b96c301 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d19fdc88190860e0c9c93ab79ce |
completed | March 31, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69cc457093188190959287a6458651c6 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:37 p.m.