Triple
T28948147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 稲城市 |
E730934
|
entity |
| Predicate | 人口属性 |
P2501
|
FINISHED |
| Object | 東京のベッドタウンとして通勤者が多い |
—
|
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: 東京のベッドタウンとして通勤者が多い | Statement: [稲城市, 人口属性, 東京のベッドタウンとして通勤者が多い]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 人口属性 Context triple: [稲城市, 人口属性, 東京のベッドタウンとして通勤者が多い]
-
A.
demographicCharacteristic
chosen
Indicates that one entity specifies or describes a demographic attribute or feature (such as age, gender, ethnicity, or similar population-related trait) of another entity.
-
B.
demographicsCharacteristic
Indicates that one entity serves as a demographic attribute or characteristic (such as age, gender, ethnicity, etc.) that describes or classifies another entity.
-
C.
demographicsDescriptor
Indicates a descriptive attribute or classification that characterizes the demographic properties of an entity or group.
-
D.
populationClass
Indicates a categorical classification of a population based on shared characteristics, status, or demographic criteria.
-
E.
populationIncludes
Indicates that a population contains or encompasses the specified individual(s) or subgroup(s) as members or elements.
- 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_69f043eb9bcc819091ac7b07aecb6475 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f65b8a9a6c819091b9ec4563704490 |
completed | May 2, 2026, 8:16 p.m. |
| PD | Predicate disambiguation | batch_69f659d02f1c8190831758ac52bb54e4 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 8:42 a.m.