Triple
T29884584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banbasa–Mahendranagar crossing |
E758973
|
entity |
| Predicate | hasNearbyUrbanCenterOnNepaliSide |
P36605
|
FINISHED |
| Object | Bhimdatta |
—
|
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: Bhimdatta | Statement: [Banbasa–Mahendranagar crossing, hasNearbyUrbanCenterOnNepaliSide, Bhimdatta]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyUrbanCenterOnNepaliSide Context triple: [Banbasa–Mahendranagar crossing, hasNearbyUrbanCenterOnNepaliSide, Bhimdatta]
-
A.
hasRegionalCenterNearby
Indicates that a regional center is located in close proximity to the referenced entity.
-
B.
isNearCapitalCity
Indicates that an entity is located close to, or in the immediate vicinity of, a capital city.
-
C.
nearbyUrbanCenter
chosen
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
D.
hasNearbyCityArea
Indicates that one area is geographically close to or adjacent to a city area.
-
E.
hasNearbyCityFunction
Indicates that one entity serves as a nearby urban center or city-like service hub for another entity.
- 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_69f2245de2f48190a481404896b56254 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fe6fea4a288190bf8615c5d6bf41b4 |
completed | May 8, 2026, 11:21 p.m. |
| PD | Predicate disambiguation | batch_69fe6f774de08190975a2393b9a1fd22 |
completed | May 8, 2026, 11:19 p.m. |
Created at: April 29, 2026, 5:59 p.m.