Triple
T31526977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poonch |
E804371
|
entity |
| Predicate | conflictAffectedArea |
P21190
|
FINISHED |
| Object | Indo-Pakistani conflicts |
—
|
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: Indo-Pakistani conflicts | Statement: [Poonch, conflictAffectedArea, Indo-Pakistani conflicts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conflictAffectedArea Context triple: [Poonch, conflictAffectedArea, Indo-Pakistani conflicts]
-
A.
regionOfConflict
Indicates that a specified region is the location where a particular conflict or dispute takes place.
-
B.
conflictRegion
chosen
Indicates that the entities are located in or associated with a geographic area characterized by active or recent conflict, tension, or hostilities.
-
C.
conflictCountry
Indicates that there is an armed conflict or war involving the referenced country as a participant.
-
D.
affectedSyrianRegion
Indicates that a specified Syrian region is impacted or influenced by a particular event, condition, or action.
-
E.
affectedCountry
Indicates that a particular country is impacted or influenced by an event, action, or condition.
- 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_69f348cf839c81908657048402f7f97b |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6d16f5cb881908eed141afaaa0b51 |
completed | May 3, 2026, 4:39 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe45554819089cbbd538d992132 |
completed | May 3, 2026, 4:32 a.m. |
Created at: April 30, 2026, 9:59 p.m.