Triple
T6569216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alewife station |
E155389
|
entity |
| Predicate | hasPassengerDropOffArea |
P40067
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Alewife station, hasPassengerDropOffArea, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassengerDropOffArea Context triple: [Alewife station, hasPassengerDropOffArea, true]
-
A.
hasDropOffArea
Indicates that an entity provides a designated area where items, passengers, or goods can be temporarily left or unloaded.
-
B.
hasPassengerPickUpDropOff
chosen
Indicates that one entity serves as a designated location or point where passengers are picked up and/or dropped off by another entity.
-
C.
hasPassengerArea
Indicates that an object or vehicle includes a designated area intended for carrying passengers.
-
D.
hasPassengerTerminal
Indicates that one entity possesses or is equipped with a passenger terminal used for boarding, alighting, or handling passengers.
-
E.
hasPassengerTerminalFacilities
Indicates that an entity provides facilities or infrastructure specifically intended for handling and serving 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_69c688151254819080387f87deab8fa7 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6cc9c6cb0819084fec8e0beb430de |
completed | March 27, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_69c6acf93cb48190b54f5dd6febd34dc |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:53 p.m.