Triple
T15955632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Izumo Airport |
E386925
|
entity |
| Predicate | distanceToMatsueKilometers |
P121117
|
FINISHED |
| Object | about 30 |
—
|
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: about 30 | Statement: [Izumo Airport, distanceToMatsueKilometers, about 30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMatsueKilometers Context triple: [Izumo Airport, distanceToMatsueKilometers, about 30]
-
A.
distanceToSapporo
Indicates the measured or calculated distance between a given entity and the location of Sapporo.
-
B.
distanceFromKochi_km
Indicates the physical distance, measured in kilometers, between a given location and Kochi.
-
C.
distanceFromNagoyaCityCenterKilometers
Indicates the distance, measured in kilometers, between an entity and the center of Nagoya City.
-
D.
distanceFromTokyo
Indicates the physical distance between a given location and Tokyo.
-
E.
distanceToKyushu
Indicates the spatial distance between a given entity’s location and the region of Kyushu.
- 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142d37cd88190ab50760f1783e20c |
completed | April 16, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69e17d48cc9c8190b03fd07ae2e9dfd8 |
completed | April 17, 2026, 12:22 a.m. |
Created at: April 10, 2026, 4:53 a.m.