Triple
T35804253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magome-juku |
E1035063
|
entity |
| Predicate | trailDistanceToTsumagoJuku |
P183694
|
FINISHED |
| Object | approximately 8 kilometers |
—
|
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 8 kilometers | Statement: [Magome-juku, trailDistanceToTsumagoJuku, approximately 8 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trailDistanceToTsumagoJuku Context triple: [Magome-juku, trailDistanceToTsumagoJuku, approximately 8 kilometers]
-
A.
distanceToMatsueKilometers
Indicates the distance, measured in kilometers, between a given entity and the location Matsue.
-
B.
distanceToIōtō
Indicates the spatial distance between a subject and the location Iōtō.
-
C.
distanceToBeppuByRoad
Indicates the road travel distance required to reach Beppu from a given location.
-
D.
distanceToSapporo
Indicates the measured or calculated distance between a given entity and the location of Sapporo.
-
E.
distanceToŌitaCityByRoad
Indicates the road travel distance between a given place and Ōita City.
- 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_69f76e169bd081909f16cd8c9ee7870c |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a283388c81908e4a9ee3369e8d6f |
completed | May 3, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69f7a070e23881909a233370acb57384 |
completed | May 3, 2026, 7:22 p.m. |
| PDg | Predicate description generation | batch_69f7a162672481909773f8383d91159a |
completed | May 3, 2026, 7:26 p.m. |
Created at: May 3, 2026, 4:06 p.m.