Triple
T28933626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bedford Park, Bronx |
E733853
|
entity |
| Predicate | hasCommuterRailStationNearby |
P149101
|
FINISHED |
| Object | Botanical Garden station |
—
|
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: Botanical Garden station | Statement: [Bedford Park, Bronx, hasCommuterRailStationNearby, Botanical Garden station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommuterRailStationNearby Context triple: [Bedford Park, Bronx, hasCommuterRailStationNearby, Botanical Garden station]
-
A.
nearCommuterRailStation
chosen
Indicates that one entity is located close to, or within a short walking distance of, a commuter rail station.
-
B.
hasNearbyRailwayStation
Indicates that a railway station is located within a short or convenient distance from the referenced entity.
-
C.
hasMBTACommuterRailTerminus
Indicates that one entity serves as the endpoint or final stop of an MBTA Commuter Rail line for the other entity.
-
D.
hasPublicTransportStop
Indicates that a location or area contains or is served by a public transport stop, such as a bus, tram, or train stop.
-
E.
hasNearbyRailway
Indicates that one entity is located close to a railway associated with or relevant to another entity.
- 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_69f05b0b49b08190b8994b339c7980f6 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_6a000fda03948190881b7275f249768f |
completed | May 10, 2026, 4:55 a.m. |
| PD | Predicate disambiguation | batch_6a000f607f1881908ee750d58da91690 |
completed | May 10, 2026, 4:53 a.m. |
Created at: April 28, 2026, 8:30 a.m.