Triple
T11309599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 寝屋川市 |
E267802
|
entity |
| Predicate | 中心市街地 |
P44319
|
FINISHED |
| Object | 寝屋川市駅周辺 |
—
|
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: 寝屋川市駅周辺 | Statement: [寝屋川市, 中心市街地, 寝屋川市駅周辺]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 中心市街地 Context triple: [寝屋川市, 中心市街地, 寝屋川市駅周辺]
-
A.
urbanDistrictType
Indicates the classification of an urban district according to its specific type or category within an administrative or planning system.
-
B.
urbanAreaType
Indicates the classification of an area based on its urban characteristics or development type (e.g., city, town, suburb, metropolitan region).
-
C.
hasStreetLayoutCenteredOn
Indicates that the spatial organization or pattern of streets in one place is arranged with a particular feature or location as its central focus or reference point.
-
D.
streetOrAreaType
chosen
Indicates the specific kind or classification of a street or area (such as avenue, boulevard, district, or zone) associated with an entity.
-
E.
centerType
Indicates the classification or category of a center (e.g., type of facility, institution, or hub) associated with an 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_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.