Triple
T936316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M7 electric multiple unit |
E20201
|
entity |
| Predicate | hasToilet |
P1976
|
FINISHED |
| Object | no (typical configuration on LIRR and Metro-North) |
—
|
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: no (typical configuration on LIRR and Metro-North) | Statement: [M7 electric multiple unit, hasToilet, no (typical configuration on LIRR and Metro-North)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasToilet Context triple: [M7 electric multiple unit, hasToilet, no (typical configuration on LIRR and Metro-North)]
-
A.
hasRestrooms
chosen
Indicates that a place or facility provides access to restroom or toilet amenities.
-
B.
hasFountain
Indicates that one entity contains, features, or is equipped with a fountain.
-
C.
has
Indicates that one entity possesses, owns, contains, or includes another entity as part of its state or composition.
-
D.
hasRoom
Indicates that an entity possesses, contains, or is associated with a specific room.
-
E.
hasNotableFacility
Indicates that an entity possesses or hosts a facility that is of particular significance, prominence, or interest.
- 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_69a493b0270c81909e6c9ce310f6aa55 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b36558588190a2a9c710073624d1 |
completed | March 1, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69a4b29b245c8190b143f28b77fede3c |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.