Triple
T9211701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kerama Islands |
E221135
|
entity |
| Predicate | distanceFromNaha |
P86883
|
FINISHED |
| Object | about 30 to 40 kilometers west |
—
|
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 to 40 kilometers west | Statement: [Kerama Islands, distanceFromNaha, about 30 to 40 kilometers west]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromNaha Context triple: [Kerama Islands, distanceFromNaha, about 30 to 40 kilometers west]
-
A.
distanceFromKochi_km
Indicates the physical distance, measured in kilometers, between a given location and Kochi.
-
B.
distanceFromTokyo
Indicates the physical distance between a given location and Tokyo.
-
C.
distanceFromMiyakoAirport
Indicates the measured distance between a given location and Miyako Airport.
-
D.
distanceToSapporo
Indicates the measured or calculated distance between a given entity and the location of Sapporo.
-
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_69ca83e9d0e081908bdb71097201a06c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd9b69838819088f33ca995fce222 |
completed | April 1, 2026, 8:39 a.m. |
| PD | Predicate disambiguation | batch_69cc660ce23c81909c7bbe10f4a05f36 |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc687067fc81909da2d78fda0cdcfb |
completed | April 1, 2026, 12:36 a.m. |
Created at: March 30, 2026, 7:27 p.m.