Triple
T32070913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jaish-e-Mohammed |
E819007
|
entity |
| Predicate | hasCarriedOutAttacksIn |
P100267
|
FINISHED |
| Object | Jammu and Kashmir |
—
|
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 and Kashmir | Statement: [Jaish-e-Mohammed, hasCarriedOutAttacksIn, Jammu and Kashmir]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCarriedOutAttacksIn Context triple: [Jaish-e-Mohammed, hasCarriedOutAttacksIn, Jammu and Kashmir]
-
A.
hasAttack
chosen
Indicates that one entity performs, possesses, or is associated with an attack directed toward another entity.
-
B.
wasAttackedIn
Indicates that an entity experienced an attack that occurred at or within a specified location or context.
-
C.
sawCombat
Indicates that an entity directly participated in active military or armed conflict.
-
D.
hasCombat
Indicates that an entity engages in, is involved with, or possesses the capability for combat or fighting interactions with other entities.
-
E.
hasFight
Indicates that one entity engages in a physical or verbal conflict with 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_69f348fecc088190af1470afe5a969f0 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fecb4d02f881909a9ee97ce98000d5 |
completed | May 9, 2026, 5:51 a.m. |
| PD | Predicate disambiguation | batch_69fec9846c1c8190b317f0711f0755db |
completed | May 9, 2026, 5:43 a.m. |
Created at: May 1, 2026, 12:23 a.m.