Triple
T11309625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 寝屋川市 |
E267802
|
entity |
| Predicate | 広域連携圏域 |
P28511
|
FINISHED |
| Object | 北河内地域 |
—
|
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: 北河内地域 | Statement: [寝屋川市, 広域連携圏域, 北河内地域]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 広域連携圏域 Context triple: [寝屋川市, 広域連携圏域, 北河内地域]
-
A.
regionOfAssociation
Indicates a broader geographic or spatial area with which an entity is functionally, contextually, or organizationally associated.
-
B.
collaborationRegion
chosen
Indicates the geographic or administrative area within which the collaboration between entities takes place or is defined.
-
C.
arealRegion
Indicates that something occupies or pertains to a specific two-dimensional geographic or spatial area.
-
D.
connectsAdministrativeArea
Indicates a relationship where one entity serves as a link or route between two administrative areas (such as regions, districts, or municipalities).
-
E.
relatedUrbanArea
Indicates that one urban area is geographically or functionally associated with another urban area, such as being nearby, connected, or part of the same broader metropolitan context.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9c0b3b88190ac0e3d6a5ad3b9bc |
completed | April 9, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69d787aa31888190860eecaa80da5b20 |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.