Triple
T31506926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nada Kenka Matsuri |
E803841
|
entity |
| Predicate | wardOrArea |
P171712
|
FINISHED |
| Object | Nada area of Himeji |
—
|
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: Nada area of Himeji | Statement: [Nada Kenka Matsuri, wardOrArea, Nada area of Himeji]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wardOrArea Context triple: [Nada Kenka Matsuri, wardOrArea, Nada area of Himeji]
-
A.
ward
Indicates that one entity is under the protection, guardianship, or custodial responsibility of another entity.
-
B.
wardNumber
Indicates the specific ward identifier or number associated with an entity, typically within an institution like a hospital or electoral district.
-
C.
lapDirection
Indicates the direction or orientation in which a lapping or overlapping action occurs between entities.
-
D.
venueArea
Indicates the physical size or spatial extent of a venue, typically measured in units such as square meters or square feet.
-
E.
navigationArea
Indicates that a specified region or space is designated for movement, routing, or pathfinding within an environment.
- 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_69f348ceb0a48190ae7feca263b6296c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a21826308190b12c2e8d6ab218d5 |
completed | May 3, 2026, 1:17 a.m. |
| PD | Predicate disambiguation | batch_69f69fe82e5c81909da9db0a2f3bba6d |
completed | May 3, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69f6a0e920cc8190a943fdd0594906c5 |
completed | May 3, 2026, 1:12 a.m. |
Created at: April 30, 2026, 9:47 p.m.