Triple
T23523904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jordan and Israel |
E574580
|
entity |
| Predicate | faceTensionsOver |
P11899
|
FINISHED |
| Object | Israeli–Palestinian violence |
—
|
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: Israeli–Palestinian violence | Statement: [Jordan and Israel, faceTensionsOver, Israeli–Palestinian violence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: faceTensionsOver Context triple: [Jordan and Israel, faceTensionsOver, Israeli–Palestinian violence]
-
A.
facesConflictWith
Indicates that one entity is in opposition, dispute, or contention with another, involving incompatible goals, interests, or actions.
-
B.
tension
chosen
Indicates a state of strain, stress, or conflict existing between entities, often involving opposing forces, interests, or emotions.
-
C.
diplomaticTensionBetween
Indicates a strained or conflict-prone diplomatic relationship existing between two entities.
-
D.
languageTension
Indicates a relationship where differing languages or language use create conflict, strain, or friction between entities.
-
E.
facedConflictOver
Indicates that two or more entities experienced opposition, dispute, or tension concerning a particular issue, resource, or situation.
- 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_69e245bb3dcc8190ba9a2b35972b58d0 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1ac71ec8881909bfb706efdc2518f |
completed | April 29, 2026, 7 a.m. |
| PD | Predicate disambiguation | batch_69f1189d75b48190a1c01928a993c9fb |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:09 p.m.