Triple
T30441773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | アメリカ合衆国ミシガン州リボニア市 |
E774463
|
entity |
| Predicate | 治安 |
P169439
|
FINISHED |
| Object | デトロイト中心部と比べると比較的治安が良いとされる |
—
|
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: デトロイト中心部と比べると比較的治安が良いとされる | Statement: [アメリカ合衆国ミシガン州リボニア市, 治安, デトロイト中心部と比べると比較的治安が良いとされる]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 治安 Context triple: [アメリカ合衆国ミシガン州リボニア市, 治安, デトロイト中心部と比べると比較的治安が良いとされる]
-
A.
regionOfCrimes
Indicates the geographic area or jurisdiction in which the crimes occurred or are attributed to an entity.
-
B.
society
Indicates a relationship in which individuals or groups are organized into a structured community bound by shared institutions, norms, or social systems.
-
C.
policeBureau
Indicates that an entity functions as or is associated with a police bureau or police department.
-
D.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
-
E.
postCrimeActivity
Indicates actions or behaviors carried out after a crime has been committed, typically in response to or as a consequence of that crime.
- F. None of above. chosen
Provenance (4 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_69f22493ef9c8190ae8c2afcb7f994c8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6869948e481908901dbda23952cc0 |
completed | May 2, 2026, 11:19 p.m. |
| PD | Predicate disambiguation | batch_69f678d2196c8190b9d0d2fcd47cc539 |
completed | May 2, 2026, 10:21 p.m. |
| PDg | Predicate description generation | batch_69f67d31cc60819084f64bd056e1ea4d |
completed | May 2, 2026, 10:39 p.m. |
Created at: April 29, 2026, 8:08 p.m.