Triple
T16967877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 津山市 |
E411588
|
entity |
| Predicate | isHistoricCastleTown |
P87637
|
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, isHistoricCastleTown, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isHistoricCastleTown Context triple: [津山市, isHistoricCastleTown, true]
-
A.
containsHistoricTown
Indicates that one entity geographically includes or encompasses a town that has recognized historical significance.
-
B.
hasCastleTownHistory
chosen
Indicates that an entity has a historical association with a castle town, such as originating from, being located in, or significantly shaped by one.
-
C.
governsHistoricTown
Indicates that one entity exercises official governing authority over a town that is recognized as historically significant.
-
D.
hasHistoricCountyTownRelation
Indicates a relationship where a town serves or has served as the historic county town (traditional administrative center) of a given county.
-
E.
containsHistoricFort
Indicates that a place or area includes within its boundaries a historic fort.
- 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.