Triple
T9859437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrew station |
E239670
|
entity |
| Predicate | hasMBTAStationCode |
P1289
|
FINISHED |
| Object | place-andrw |
—
|
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: place-andrw | Statement: [Andrew station, hasMBTAStationCode, place-andrw]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMBTAStationCode Context triple: [Andrew station, hasMBTAStationCode, place-andrw]
-
A.
hasStationCode
chosen
Indicates that an entity is associated with a specific station identification code.
-
B.
hasAdjacentStationOnMattapanLine
Indicates that one station is directly next to another station along the Mattapan Line, with no other stations in between.
-
C.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
-
D.
terminusStation
Indicates that a station serves as the final endpoint or terminal stop for a given route or service.
-
E.
isTransportationHubCodeFor
Indicates that a given code uniquely identifies and represents a specific transportation hub, such as a station, airport, or terminal.
- 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_69ca84e6493081909cf58c8d42ea856b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb39b06b48190ab53ff00ff0513ca |
completed | April 2, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69cd1d7621d48190aa6a6f34399514b0 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:35 p.m.