Triple
T9346156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fukuyama |
E224894
|
entity |
| Predicate | hasCastleTownHistory |
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: [Fukuyama, hasCastleTownHistory, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCastleTownHistory Context triple: [Fukuyama, hasCastleTownHistory, true]
-
A.
containsHistoricTown
Indicates that one entity geographically includes or encompasses a town that has recognized historical significance.
-
B.
hasMarketTownHistory
Indicates that an entity has a historical association with functioning as a market town or possessing recognized market-town status in the past.
-
C.
hasCastleRemains
Indicates that one entity possesses or contains the remaining structures or ruins of a castle associated with it.
-
D.
hasFamousCastle
Indicates that an entity possesses or is the location of a castle that is widely recognized or renowned.
-
E.
hasHistoricCity
Indicates that an entity possesses, contains, or is associated with a city recognized for its historical significance.
- 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_69ca842993248190a79ab06968994b86 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4f0e2ccc8190a68f1c96c0886660 |
completed | April 1, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69cc7a66aef08190b8d668cff5b04f5f |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc94b796788190816b71b1e9996288 |
completed | April 1, 2026, 3:44 a.m. |
Created at: March 30, 2026, 7:41 p.m.