Triple
T16404918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ōita Airport |
E398400
|
entity |
| Predicate | distanceToŌitaCityByRoad |
P123298
|
FINISHED |
| Object | approximately 30 km |
—
|
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 30 km | Statement: [Ōita Airport, distanceToŌitaCityByRoad, approximately 30 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToŌitaCityByRoad Context triple: [Ōita Airport, distanceToŌitaCityByRoad, approximately 30 km]
-
A.
distanceFromKochi_km
Indicates the physical distance, measured in kilometers, between a given location and Kochi.
-
B.
distanceToKyushu
Indicates the spatial distance between a given entity’s location and the region of Kyushu.
-
C.
distanceFromNagoyaCityCenterKilometers
Indicates the distance, measured in kilometers, between an entity and the center of Nagoya City.
-
D.
distanceToMatsueKilometers
Indicates the distance, measured in kilometers, between a given entity and the location Matsue.
-
E.
distanceToIōtō
Indicates the spatial distance between a subject and the location Iōtō.
- 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_69d87f2950248190bc8ad9b9bebdc8c8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e327d1f16481909adb19dab86dcc72 |
completed | April 18, 2026, 6:42 a.m. |
| PD | Predicate disambiguation | batch_69e226fe1dd08190865c181721f8c348 |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24555bb6c8190977cf5c5f9149056 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:09 a.m.