Triple
T20647772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 15th Street–Prospect Park |
E507401
|
entity |
| Predicate | stationCodeType |
P1289
|
FINISHED |
| Object | internal NYCT code |
—
|
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: internal NYCT code | Statement: [15th Street–Prospect Park, stationCodeType, internal NYCT code]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stationCodeType Context triple: [15th Street–Prospect Park, stationCodeType, internal NYCT code]
-
A.
stationType
Indicates the specific category or classification of a station based on its function, services, or operational characteristics.
-
B.
stationNumber
Indicates the specific station identifier or code assigned to an entity within a system or network.
-
C.
hasStationCode
chosen
Indicates that an entity is associated with a specific station identification code.
-
D.
stationName
Indicates the name assigned to a particular station in the relationship.
-
E.
railwayStationCodeFor
Indicates that one entity is the designated railway station code corresponding to a particular railway station.
- 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_69e0b4be702c8190a3d2410a881d310a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6af1fbfa881908a5b9db143e362d0 |
completed | April 20, 2026, 10:56 p.m. |
| PD | Predicate disambiguation | batch_69e5c0315f5081908098707c6455e56e |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 11:43 a.m.