Triple
T35455745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 土佐国 |
E1024767
|
entity |
| Predicate | hasHistoricalProvinceCode |
P28337
|
FINISHED |
| Object | Tosa |
—
|
NE NERFINISHED |
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: Tosa | Statement: [土佐国, hasHistoricalProvinceCode, Tosa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricalProvinceCode Context triple: [土佐国, hasHistoricalProvinceCode, Tosa]
-
A.
historicalRegionCode
chosen
Indicates that an entity is associated with a specific code identifying a historical region.
-
B.
hasHistoricalCountrySubdivision
Indicates that one entity was a territorial or administrative subdivision of a historical country.
-
C.
hasHistoricCountyCode
Indicates that an entity is associated with a specific historic county, identified by its county code.
-
D.
hasHistoricalRegionType
Indicates that a historical region is associated with a specific type or classification of historical region.
-
E.
hasHomeRegionHistorical
Indicates that an entity is historically associated with or originates from a particular home region.
- 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_69f76df92f108190817222e520e22268 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff48199b1c8190bb05872f8a4f4673 |
completed | May 9, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69ff4746b1cc8190854f70a124df7d04 |
completed | May 9, 2026, 2:40 p.m. |
Created at: May 3, 2026, 4:04 p.m.