Triple
T25527967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 7 Subway Extension |
E639825
|
entity |
| Predicate | numberOfNewStations |
P183471
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [7 Subway Extension, numberOfNewStations, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfNewStations Context triple: [7 Subway Extension, numberOfNewStations, 1]
-
A.
numberOfStations
Indicates the total count of stations associated with or contained by a given entity.
-
B.
numberOfUndergroundStations
Indicates the total count of underground (subway/metro) stations associated with a given entity.
-
C.
numberOfStationsOpenedInPhase1
Indicates the total count of stations that were opened during the first phase of a project or rollout.
-
D.
reopenedStation
Indicates that a station which was previously closed has been opened again for use or service.
-
E.
relatedStationNumber
Indicates that there is an associated or corresponding station identified by a particular station number.
- 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_69e75dbf3f9c8190b3f2a75d1b75d127 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f7a01efcc08190bba489a9099b8684 |
completed | May 3, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69f79e4888248190be2f63cdfb5cd7b7 |
completed | May 3, 2026, 7:13 p.m. |
| PDg | Predicate description generation | batch_69f79f477c4c8190a35cb6d87b1dcbd1 |
completed | May 3, 2026, 7:17 p.m. |
Created at: April 21, 2026, 3:12 p.m.