Triple
T28096937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East 180th Street station |
E710117
|
entity |
| Predicate | hasAdjacentRailFacility |
P231
|
FINISHED |
| Object | East 180th Street Yard |
—
|
NE NERFINISHED |
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: East 180th Street Yard | Statement: [East 180th Street station, hasAdjacentRailFacility, East 180th Street Yard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdjacentRailFacility Context triple: [East 180th Street station, hasAdjacentRailFacility, East 180th Street Yard]
-
A.
hasRailFacility
Indicates that an entity possesses or is served by a rail-related facility, such as a railway station, terminal, or yard.
-
B.
hasAdjacentRailService
Indicates that one location has rail service situated directly next to or immediately bordering it.
-
C.
hasNearbyRailway
Indicates that one entity is located close to a railway associated with or relevant to another entity.
-
D.
adjacentToInfrastructure
chosen
Indicates that one entity is located directly next to or in immediate proximity to a piece of infrastructure.
-
E.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail 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_69ef9b70fd108190a875953b2e50ca91 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f70e8755a48190931eaa77946f9460 |
completed | May 3, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f70abc00848190a1c3f495ef6c8dc6 |
completed | May 3, 2026, 8:43 a.m. |
Created at: April 27, 2026, 9:02 p.m.