Triple
T34857114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 櫛稲田姫命 |
E1004755
|
entity |
| Predicate | 地域的関連 |
P12445
|
FINISHED |
| Object | 出雲国 |
—
|
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: 出雲国 | Statement: [櫛稲田姫命, 地域的関連, 出雲国]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 地域的関連 Context triple: [櫛稲田姫命, 地域的関連, 出雲国]
-
A.
関与地域
Indicates a geographical area or region that is involved in, affected by, or relevant to a particular activity, event, or relationship.
-
B.
所在地エリア
Indicates the geographical area or region in which an entity is located or based.
-
C.
regionallyAssociatedWith
chosen
Indicates that two entities are connected or related based on sharing the same or overlapping geographic or regional context.
-
D.
typicalGeographicalAssociation
Indicates a usual or characteristic geographical connection between entities, such as a place commonly associated with a person, group, or phenomenon.
-
E.
geographicRelevance
Indicates that something has a meaningful connection or applicability to a specific geographic area or 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_69f76dba76f0819090643cba102c41ec |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782f4f10081908f97f6d0d2dbeec7 |
completed | May 3, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69f780ff71cc8190a67e71076fbad81a |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.