Triple
T8708967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Broadway station (LIRR) |
E206723
|
entity |
| Predicate | servesLocalPassengers |
P60095
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Broadway station (LIRR), servesLocalPassengers, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesLocalPassengers Context triple: [Broadway station (LIRR), servesLocalPassengers, yes]
-
A.
servesLocalTrains
chosen
Indicates that a station or facility provides service or stops specifically for local (non-express) train routes.
-
B.
takesPassengersCloseTo
Indicates that a transport service carries passengers to a location that is near, but not necessarily exactly at, a specified destination.
-
C.
hasPassengerServicesTo
Indicates that a transportation provider operates passenger services connecting one location or entity to another.
-
D.
operatedPassengerServices
Indicates that an entity provided and managed transportation services specifically for carrying passengers.
-
E.
hasPassengerTerminalFunction
Indicates that something serves the role or performs the function of a passenger terminal, supporting the handling and movement of passengers.
- 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_69ca835645e881908f00e3c8b51da81d |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc58ffa6a481908866b6239d1d9b92 |
completed | March 31, 2026, 11:30 p.m. |
| PD | Predicate disambiguation | batch_69cc456bda508190a9aa0fb92760739e |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:35 p.m.