Triple
T29154037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Kisokoma |
E738987
|
entity |
| Predicate | nearestRopewayStation |
P173256
|
FINISHED |
| Object | Senjojiki 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: Senjojiki Station | Statement: [Mount Kisokoma, nearestRopewayStation, Senjojiki Station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearestRopewayStation Context triple: [Mount Kisokoma, nearestRopewayStation, Senjojiki Station]
-
A.
nearestEntranceStation
Indicates that one station is the closest entrance station to a given location or entity compared to all other candidate stations.
-
B.
nearestPassengerRailStation
Indicates that one entity is the closest passenger rail station in distance to another entity.
-
C.
nearestRailwayTerminus
Indicates that one location is the closest railway terminus to another specified place.
-
D.
operatorOfNearestStation
Indicates that an entity is the organization or operator responsible for managing the station that is geographically closest to a given reference point or entity.
-
E.
nearestSuburbanRailwayStation
Indicates the relationship where a given place is associated with the suburban railway station that is geographically closest 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_69f07cb46f148190874eb8576a447567 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f6b342499c8190b85009a3f0f179e4 |
completed | May 3, 2026, 2:30 a.m. |
| PD | Predicate disambiguation | batch_69f6b14d7d508190bc7d4c89dfba4a32 |
completed | May 3, 2026, 2:22 a.m. |
| PDg | Predicate description generation | batch_69f6b2a31e008190aacef03c2ebe5787 |
completed | May 3, 2026, 2:27 a.m. |
Created at: April 28, 2026, 11:44 a.m.