Triple
T11309813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 淀川 |
E267806
|
entity |
| Predicate | 関連都市圏 |
P92119
|
FINISHED |
| Object | 京阪神大都市圏 |
—
|
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: 京阪神大都市圏 | Statement: [淀川, 関連都市圏, 京阪神大都市圏]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 関連都市圏 Context triple: [淀川, 関連都市圏, 京阪神大都市圏]
-
A.
relatedUrbanArea
chosen
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.
-
B.
hasNearbyCityArea
Indicates that one area is geographically close to or adjacent to a city area.
-
C.
formsUrbanAreaWith
Indicates that two or more settlements are geographically and functionally connected so that together they constitute a single continuous urban area.
-
D.
regionallyAssociatedWith
Indicates that two entities are connected or related based on sharing the same or overlapping geographic or regional context.
-
E.
macroArea
Indicates a broad geographic or regional grouping within which an entity (such as a language or location) is situated.
- 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.