Triple
T10001504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wakefield–241st Street |
E197337
|
entity |
| Predicate | hasStationCodeType |
P57418
|
FINISHED |
| Object | internal MTA 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 MTA code | Statement: [Wakefield–241st Street, hasStationCodeType, internal MTA code]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStationCodeType Context triple: [Wakefield–241st Street, hasStationCodeType, internal MTA code]
-
A.
hasStationCode
Indicates that an entity is associated with a specific station identification code.
-
B.
hasStationCodeSystem
chosen
Indicates that an entity uses or is associated with a particular system for assigning or managing station codes.
-
C.
hasStationCodePrefix
Indicates that one entity’s station code begins with the prefix specified by the other entity.
-
D.
isPassengerStationCode
Indicates that a given code is officially assigned to identify a particular passenger station.
-
E.
hasStationFunction
Indicates that an entity serves in a particular functional role or capacity at a 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_69ca82f3b61c81908ecc2c1c96dbc2e4 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdcc8f50888190b2f1c5240cb58e4f |
completed | April 2, 2026, 1:55 a.m. |
| PD | Predicate disambiguation | batch_69cd1da2cf9081908a6c0eb5247d0bc2 |
completed | April 1, 2026, 1:29 p.m. |
Created at: March 30, 2026, 8:51 p.m.