Triple
T6485268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kiryat Shmona |
E146492
|
entity |
| Predicate | conflictExposure |
P1397
|
FINISHED |
| Object | frequent shelling in Arab–Israeli 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: frequent shelling in Arab–Israeli conflicts | Statement: [Kiryat Shmona, conflictExposure, frequent shelling in Arab–Israeli conflicts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conflictExposure Context triple: [Kiryat Shmona, conflictExposure, frequent shelling in Arab–Israeli conflicts]
-
A.
conflictIn
Indicates that one entity is involved in, associated with, or occurs within a particular conflict or dispute.
-
B.
conflictSpecific
Indicates a specific, concrete instance or type of conflict that exists between the related entities.
-
C.
conflictBelligerent
Indicates that an entity is a participating belligerent (e.g., a country, group, or force) in a specific conflict.
-
D.
conflictType
chosen
Indicates the specific kind or category of conflict that characterizes the relationship or interaction between entities.
-
E.
conflictExperience
Indicates that an entity has undergone or been involved in a conflict, such as a dispute, struggle, or confrontation.
- 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_69c0090158c08190af0df9a2348d2d52 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a6efe1881909a044b1cdaa511af |
completed | March 22, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69c0673f6d48819080e10c85155c7195 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:52 p.m.