Triple
T25137807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaladagi |
E629707
|
entity |
| Predicate | hasHistoricalCountrySubdivision |
P167708
|
FINISHED |
| Object | Bombay Presidency |
—
|
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: Bombay Presidency | Statement: [Kaladagi, hasHistoricalCountrySubdivision, Bombay Presidency]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricalCountrySubdivision Context triple: [Kaladagi, hasHistoricalCountrySubdivision, Bombay Presidency]
-
A.
hasHistoricalDivision
Indicates that an entity has undergone a formal separation or split into distinct parts at some point in its history.
-
B.
hasHistoricTerritory
Indicates that an entity possesses or claims a territory that it historically occupied, controlled, or was associated with in the past.
-
C.
hasHomeRegionHistorical
Indicates that an entity is historically associated with or originates from a particular home region.
-
D.
historicalRegionCode
Indicates that an entity is associated with a specific code identifying a historical region.
-
E.
hasHistoricalRegionType
Indicates that a historical region is associated with a specific type or classification of historical region.
- 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_69e2ff338250819096ff6c8892804389 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f66cf092c881908d7034c9c2bc61d5 |
completed | May 2, 2026, 9:30 p.m. |
| PD | Predicate disambiguation | batch_69f66abddc448190a488852f8abdeb2c |
completed | May 2, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69f66c59de9881909ebbb7b0ae7ab495 |
completed | May 2, 2026, 9:27 p.m. |
Created at: April 18, 2026, 6:29 a.m.