Triple
T11969749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kawanishi |
E284884
|
entity |
| Predicate | majorUrbanCenterDistance |
P60767
|
FINISHED |
| Object | approximately 20 km from Osaka |
—
|
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: approximately 20 km from Osaka | Statement: [Kawanishi, majorUrbanCenterDistance, approximately 20 km from Osaka]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorUrbanCenterDistance Context triple: [Kawanishi, majorUrbanCenterDistance, approximately 20 km from Osaka]
-
A.
distanceFromMajorCity
chosen
Indicates the measured distance between a given location and a specified major city.
-
B.
distanceBetweenHomeCities
Indicates the measured spatial distance separating the home cities of two entities.
-
C.
districtHeadquartersDistance
Indicates the distance between a place and its corresponding district headquarters.
-
D.
distanceFromDowntown
Indicates the physical distance between a given location and the central downtown area.
-
E.
distanceFromCapital
Indicates the measured distance between a given location and the capital city of its corresponding region or country.
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9037bee54819085242a3ef3e286f9 |
completed | April 10, 2026, 2:04 p.m. |
| PD | Predicate disambiguation | batch_69d8bb40f30c8190a0e0719bd67542bf |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:46 p.m.