Triple
T8742751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York City public transportation network |
E207542
|
entity |
| Predicate | subwayStationsApprox |
P84596
|
FINISHED |
| Object | over 470 stations |
—
|
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: over 470 stations | Statement: [New York City public transportation network, subwayStationsApprox, over 470 stations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subwayStationsApprox Context triple: [New York City public transportation network, subwayStationsApprox, over 470 stations]
-
A.
subwayStation
Indicates that one entity is a subway station associated with, located in, or serving the other entity.
-
B.
nearMetroStation
Indicates that one entity is located close to or within a short walking distance of a metro (subway) station.
-
C.
nearestUndergroundStation
Indicates the relationship where a specific underground (subway/metro) station is the closest one in distance to a given location or entity.
-
D.
nearestEntranceStation
Indicates that one station is the closest entrance station to a given location or entity compared to all other candidate stations.
-
E.
nearestMajorMetro
Indicates the relationship where a given location is associated with the closest large metropolitan area to it.
- F. None of above. chosen
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_69ca835a03a081909d4d4cd01a18c9fb |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d71619481909fc4d87af3d01432 |
completed | March 31, 2026, 11:49 p.m. |
| PD | Predicate disambiguation | batch_69cc457322b481908712a9630a17b954 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc572d99bc819097f36b140c2ee1ce |
completed | March 31, 2026, 11:22 p.m. |
Created at: March 30, 2026, 6:38 p.m.