Triple
T3518281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alstom Citadis |
E74358
|
entity |
| Predicate | operatorBenefit |
P2188
|
FINISHED |
| Object | high passenger capacity |
—
|
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: high passenger capacity | Statement: [Alstom Citadis, operatorBenefit, high passenger capacity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatorBenefit Context triple: [Alstom Citadis, operatorBenefit, high passenger capacity]
-
A.
exclusiveBenefit
Indicates that a benefit is provided to one party or group in a way that excludes others from receiving the same advantage.
-
B.
hasBenefit
chosen
Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
-
C.
benefits
Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or action.
-
D.
relatedBenefit
Indicates that one entity provides an advantage, gain, or positive outcome that is connected or attributable to another entity.
-
E.
benefitsState
Indicates that one entity provides an advantage, improvement, or positive outcome to a state or governmental 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_69ad85cfb5c881909c9a2edd9d6043cc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc32f90081908960acb3e94402be |
completed | March 8, 2026, 6:13 p.m. |
| PD | Predicate disambiguation | batch_69adae10689c8190b7dc6d7daa8295b6 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:19 p.m.