Triple
T21477978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kulgam district |
E529912
|
entity |
| Predicate | hasMajorTown |
P316
|
FINISHED |
| Object | Qazigund |
—
|
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: Qazigund | Statement: [Kulgam district, hasMajorTown, Qazigund]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Qazigund Context triple: [Kulgam district, hasMajorTown, Qazigund]
-
A.
Qazigund
chosen
Qazigund is a town in the Kashmir Valley of northern India, known as a key transit point and gateway between the Jammu region and the Kashmir Valley.
-
B.
Piranshahr
Piranshahr is a predominantly Kurdish city in northwestern Iran known for its mountainous surroundings and role as a regional commercial center.
-
C.
Qaen
Qaen is a historic city in eastern Iran known as a regional center for saffron production and traditional crafts.
-
D.
Minab
Minab is a city in southern Iran known for its agriculture, traditional markets, and proximity to the Persian Gulf.
-
E.
Farashband
Farashband is a small city in southern Iran known for its location within Fars Province and its surrounding agricultural and pastoral landscapes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c459acb481909bb6ee452a0045c7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea1951fc8190910f634327aa5c3f |
completed | April 23, 2026, 9:44 a.m. |
Created at: April 16, 2026, 6:20 p.m.