Triple
T8655295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asago |
E205398
|
entity |
| Predicate | hasNeighboringPrefecture |
P43294
|
FINISHED |
| Object | Tottori Prefecture |
—
|
NE NERFINISHED |
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: Tottori Prefecture | Statement: [Asago, hasNeighboringPrefecture, Tottori Prefecture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNeighboringPrefecture Context triple: [Asago, hasNeighboringPrefecture, Tottori Prefecture]
-
A.
hasNearbyPrefecture
chosen
Indicates that one administrative region has another prefecture located geographically close to it.
-
B.
hasPrefecture
Indicates that one administrative region or country possesses or is associated with a specific prefecture as a subordinate territorial unit.
-
C.
adjacentProvince
Indicates that two provinces share a common boundary and are directly next to each other geographically.
-
D.
neighboringRegion
Indicates that two regions share a common boundary or are directly adjacent to each other geographically.
-
E.
prefectureCapitalNearby
Indicates that a prefecture’s capital city is geographically close to the referenced location.
- 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_69ca8350897c819086cde7596fbe5fe7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc4844586081909b687e278496eefa |
completed | March 31, 2026, 10:18 p.m. |
| PD | Predicate disambiguation | batch_69cc45619460819091e83ffdec99c865 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:29 p.m.