Triple
T8923031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Court Square (IND Crosstown Line) |
E212470
|
entity |
| Predicate | hasStationComplexRole |
P74029
|
FINISHED |
| Object | northern terminal for G train in Queens |
—
|
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: northern terminal for G train in Queens | Statement: [Court Square (IND Crosstown Line), hasStationComplexRole, northern terminal for G train in Queens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStationComplexRole Context triple: [Court Square (IND Crosstown Line), hasStationComplexRole, northern terminal for G train in Queens]
-
A.
stationComplex
Indicates a relationship where one entity is a station complex that encompasses or is associated with another station-related entity.
-
B.
hasStationFunction
chosen
Indicates that an entity serves in a particular functional role or capacity at a station.
-
C.
hasStationStructure
Indicates that an entity possesses or is associated with a particular station-related physical structure.
-
D.
hasComponentStation
Indicates that an entity includes or is associated with a specific station as one of its component parts.
-
E.
hasStationBuilding
Indicates that a station is associated with or includes a station building as part of its facilities.
- 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_69ca839481d48190b42b037e0d0f636c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc665143688190872c681f4299bd9f |
completed | April 1, 2026, 12:26 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed0ef3c81908cc69eac852ee12a |
completed | March 31, 2026, 11:54 p.m. |
Created at: March 30, 2026, 6:56 p.m.