Triple
T35882158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R45 |
E1037538
|
entity |
| Predicate | associatedStationBorough |
P56654
|
FINISHED |
| Object | Brooklyn |
E5446
|
NE 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: Brooklyn | Statement: [R45, associatedStationBorough, Brooklyn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedStationBorough Context triple: [R45, associatedStationBorough, Brooklyn]
-
A.
stationBorough
chosen
Indicates the borough or administrative district in which a station is located.
-
B.
associatedStation
Indicates a relationship where one entity is linked or connected to a particular station as its relevant or related station.
-
C.
adjacentStationOnBMTBroadwayLine
Indicates that one station is directly next to another station along the BMT Broadway subway line, with no other stations in between.
-
D.
hasBoroughEndpoint
Indicates that something has an endpoint located within a specific borough.
-
E.
hasBoroughEquivalent
Indicates that one administrative area corresponds functionally or hierarchically to a borough in another jurisdiction or classification system.
- F. None of above.
Provenance (4 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_69f76e1f4d748190bb55594d8441d70e |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a38b6e3da6881909b46a21c3c54c1da |
completed | June 22, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:06 p.m.