Triple
T8658479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shahid Haghani Metro Station |
E205482
|
entity |
| Predicate | isStationOn |
P30882
|
FINISHED |
| Object | north–south axis of Tehran Metro |
—
|
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: north–south axis of Tehran Metro | Statement: [Shahid Haghani Metro Station, isStationOn, north–south axis of Tehran Metro]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isStationOn Context triple: [Shahid Haghani Metro Station, isStationOn, north–south axis of Tehran Metro]
-
A.
isLocalStation
Indicates that a station operates primarily within a limited local area or serves as a stop on a local (rather than regional or long-distance) service.
-
B.
isLocalStationFor
Indicates that a station serves a specific local area or locality as its primary service point.
-
C.
isOn
Indicates that one entity is physically positioned above and in contact with the top surface of another entity.
-
D.
hasStationFunction
Indicates that an entity serves in a particular functional role or capacity at a station.
-
E.
isMajorStationOn
chosen
Indicates that a station serves as a primary or significant stop on a particular route or line.
- 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_69ca8350897c819086cde7596fbe5fe7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc486d576081908ad28749c7971432 |
completed | March 31, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69cc4564e018819081036722f3e42a71 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:30 p.m.