Triple
T27910590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sialkot–Jammu sector crossings |
E705914
|
entity |
| Predicate | nearbyCityOnIndianSide |
P85285
|
FINISHED |
| Object | Jammu |
—
|
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: Jammu | Statement: [Sialkot–Jammu sector crossings, nearbyCityOnIndianSide, Jammu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyCityOnIndianSide Context triple: [Sialkot–Jammu sector crossings, nearbyCityOnIndianSide, Jammu]
-
A.
nearbyIndianTown
Indicates that one location is a town in India situated close to the referenced place.
-
B.
nearbyTownPakistaniSide
Indicates that one location is a nearby town situated on the Pakistani side relative to another reference point or boundary.
-
C.
nearCityInPakistan
Indicates that one entity is located close to, or in the vicinity of, a specified city within Pakistan.
-
D.
hasBorderTownOnIndianSide
chosen
Indicates that a location has a corresponding town situated on the Indian side of an international border.
-
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_69ef96b5aad08190be36a277c31e7004 |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f78c61ed4c8190ad84c918fa9af55a |
completed | May 3, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69f78b8cb3a881909ebaac1b503988c2 |
completed | May 3, 2026, 5:53 p.m. |
Created at: April 27, 2026, 6:49 p.m.