Triple
T13591032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Talacauvery |
E324691
|
entity |
| Predicate | nearestTownDistance |
P110200
|
FINISHED |
| Object | about 48 kilometres from Madikeri |
—
|
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: about 48 kilometres from Madikeri | Statement: [Talacauvery, nearestTownDistance, about 48 kilometres from Madikeri]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearestTownDistance Context triple: [Talacauvery, nearestTownDistance, about 48 kilometres from Madikeri]
-
A.
nearestCityCenterDistance
Indicates the distance from a given location to the closest city center.
-
B.
nearestTownCenter
Indicates that one location is the closest town center to another specified point or area.
-
C.
hasNearestLargerSettlement
Indicates that one settlement is associated with the geographically closest settlement that is larger in size or population.
-
D.
hasNearbyTown
Indicates that one location has a town situated close to it in geographic proximity.
-
E.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb056ce088190a6feb4266633d18b |
completed | April 12, 2026, 2:46 p.m. |
| PD | Predicate disambiguation | batch_69dbae18eaf48190809e8b365856cde9 |
completed | April 12, 2026, 2:37 p.m. |
| PDg | Predicate description generation | batch_69dbaf9f3bdc8190838539aaef1f422b |
completed | April 12, 2026, 2:43 p.m. |
Created at: April 9, 2026, 9:49 p.m.