Triple
T27910589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sialkot–Jammu sector crossings |
E705914
|
entity |
| Predicate | nearbyCityOnPakistaniSide |
P97001
|
FINISHED |
| Object | Sialkot |
—
|
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: Sialkot | Statement: [Sialkot–Jammu sector crossings, nearbyCityOnPakistaniSide, Sialkot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyCityOnPakistaniSide Context triple: [Sialkot–Jammu sector crossings, nearbyCityOnPakistaniSide, Sialkot]
-
A.
nearbyTownPakistaniSide
Indicates that one location is a nearby town situated on the Pakistani side relative to another reference point or boundary.
-
B.
nearCityInPakistan
chosen
Indicates that one entity is located close to, or in the vicinity of, a specified city within Pakistan.
-
C.
distanceFromKarachi
Indicates the measured spatial distance between a given entity’s location and the city of Karachi.
-
D.
closestMajorSettlementAfghanistan
Indicates the nearest major Afghan settlement (such as a large town or city) to a given location.
-
E.
distanceFromMuzaffarabad_km
Indicates the physical distance, measured in kilometers, between an entity’s location and Muzaffarabad.
- 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_69f7886be6d8819095ec62e4f2cee858 |
completed | May 3, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69f7841440f48190b4346c08855951d2 |
completed | May 3, 2026, 5:21 p.m. |
Created at: April 27, 2026, 6:49 p.m.