Triple
T7480588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kashiba |
E176745
|
entity |
| Predicate | locatedInPartOfPrefecture |
P68954
|
FINISHED |
| Object | northwestern Nara Prefecture |
—
|
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: northwestern Nara Prefecture | Statement: [Kashiba, locatedInPartOfPrefecture, northwestern Nara Prefecture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInPartOfPrefecture Context triple: [Kashiba, locatedInPartOfPrefecture, northwestern Nara Prefecture]
-
A.
partOfPrefecture
chosen
Indicates that one entity is a subdivision or component that belongs administratively or geographically to a given prefecture.
-
B.
locatedInPrefectureLevelCity
Indicates that one entity is geographically situated within the jurisdiction or boundaries of a prefecture-level city.
-
C.
locatedInPrefectureCapitalRegion
Indicates that the subject is geographically situated within the capital region of a given prefecture.
-
D.
hasPrefecture
Indicates that one administrative region or country possesses or is associated with a specific prefecture as a subordinate territorial unit.
-
E.
hostPrefecture
Indicates the prefecture that serves as the host location for an event, activity, or entity.
- 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_69c69f236ce08190a04d7679f03b29b2 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f532f4488190b6edaa96099c3b8f |
completed | March 27, 2026, 9:22 p.m. |
| PD | Predicate disambiguation | batch_69c6f03d967081908a8e696ff9693b90 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:42 p.m.