Triple
T37061666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 守口市 |
E917337
|
entity |
| Predicate | 人口動態 |
P46033
|
FINISHED |
| Object | 大阪市のベッドタウンとして人口集積が進んだ |
—
|
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: 大阪市のベッドタウンとして人口集積が進んだ | Statement: [守口市, 人口動態, 大阪市のベッドタウンとして人口集積が進んだ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 人口動態 Context triple: [守口市, 人口動態, 大阪市のベッドタウンとして人口集積が進んだ]
-
A.
人口規模
Indicates the relationship describing the size or scale of a population associated with an entity (such as a region, city, or group).
-
B.
population
Indicates the total number of individuals living in or present within a specified area or group.
-
C.
populationEvent
chosen
Indicates an event or occurrence that causes a change in the size, composition, or distribution of a population.
-
D.
populationFocus
Indicates that something is primarily directed toward, concerned with, or designed for a particular population or demographic group.
-
E.
permanentPopulation
Indicates that an entity has a stable, long-term resident population rather than a temporary or transient presence.
- 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_69f76e95fa40819091e14681087ae5e4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb34e5576881909394355c8ec6ddd2 |
completed | May 6, 2026, 12:32 p.m. |
| PD | Predicate disambiguation | batch_69fb2f6171e88190bf1e0ee6a644b6a9 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4:14 p.m.