Triple
T29783174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hakutaka |
E756181
|
entity |
| Predicate | usesTrainsetFormation |
P142978
|
FINISHED |
| Object | 12-car trainsets |
—
|
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: 12-car trainsets | Statement: [Hakutaka, usesTrainsetFormation, 12-car trainsets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTrainsetFormation Context triple: [Hakutaka, usesTrainsetFormation, 12-car trainsets]
-
A.
canFormTrainOf
Indicates that one entity is capable of being physically or logically connected with another to form a continuous train or sequence.
-
B.
hasCarFormation
chosen
Indicates that one entity is arranged or organized into a specific configuration or sequence of cars relative to another entity.
-
C.
numberOfTrainsetsBuilt
Indicates the total count of trainsets that have been constructed or produced.
-
D.
railForm
Indicates that one entity takes the form of, or is structured as, a rail or rail-like configuration in relation to another entity.
-
E.
trainTypeUsed
Indicates that a specific type or category of train is employed or operated in a given context or service.
- 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_69f22451fb748190bbdbab401280affb |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f71996e1a48190ac59a1d66d7c44e8 |
completed | May 3, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69f71820c6c88190ab38b4fa626d22cc |
completed | May 3, 2026, 9:40 a.m. |
Created at: April 29, 2026, 5:06 p.m.