Triple
T16967887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 津山市 |
E411588
|
entity |
| Predicate | hasTraditionalStreetscapes |
P108672
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [津山市, hasTraditionalStreetscapes, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraditionalStreetscapes Context triple: [津山市, hasTraditionalStreetscapes, true]
-
A.
hasHistoricStreet
Indicates that an entity is associated with or located on a street that has recognized historical significance.
-
B.
streetscapeStyle
chosen
Indicates the characteristic visual and design style that defines the overall appearance and layout of a street and its surrounding public realm.
-
C.
isPartOfStreetscape
Indicates that something forms a component or element within the overall layout or visual composition of a streetscape.
-
D.
hasTreeLinedStreets
Indicates that the streets in a given area are lined or bordered with trees along their sides.
-
E.
hasHistoricDistrict
Indicates that an entity possesses or contains a designated historic district within its boundaries or domain.
- 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_69d886c9c9d481909afe222093641cae |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d0a6f628819080db47285954729a |
completed | April 18, 2026, 6:42 p.m. |
| PD | Predicate disambiguation | batch_69e35d4dff4881909b384e30f2d36bff |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:31 a.m.