Triple
T6205364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kargil War |
E138730
|
entity |
| Predicate | PakistaniFatalitiesApprox |
P700
|
FINISHED |
| Object | around 400–700 (estimates vary) |
—
|
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: around 400–700 (estimates vary) | Statement: [Kargil War, PakistaniFatalitiesApprox, around 400–700 (estimates vary)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: PakistaniFatalitiesApprox Context triple: [Kargil War, PakistaniFatalitiesApprox, around 400–700 (estimates vary)]
-
A.
AfghanCasualties
Indicates the number or occurrence of casualties suffered by Afghan individuals or forces in a given event or context.
-
B.
deathTollEstimate
chosen
Indicates an estimated number of deaths attributed to a particular event, cause, or period.
-
C.
nativeCasualties
Indicates that native or indigenous people suffered deaths or injuries as a result of a particular event, action, or conflict.
-
D.
areaRankInPakistan
Indicates the relative position of an entity when all entities in Pakistan are ordered by their area size.
-
E.
militaryCasualtiesEstimate
Indicates an estimated number of people killed, wounded, or missing as a result of military conflict or operations.
- 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_69c008acbea48190991c6b834bb45d65 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0626d96ec8190816c00c44668177d |
completed | March 22, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69c055fdea3c81908f5d910f0d36234a |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:20 p.m.