Triple
T15914245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avner Kaufman |
E385928
|
entity |
| Predicate | primaryAntagonistForce |
P81119
|
FINISHED |
| Object | Black September members |
—
|
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: Black September members | Statement: [Avner Kaufman, primaryAntagonistForce, Black September members]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryAntagonistForce Context triple: [Avner Kaufman, primaryAntagonistForce, Black September members]
-
A.
primaryAntagonistType
Indicates the role or category of the main opposing force or adversary that serves as the central source of conflict.
-
B.
primaryAntagonists
chosen
Indicates that the referenced entities serve as the main opposing or adversarial forces in relation to a specified subject or narrative.
-
C.
primaryAntagonisticRealmIn
Indicates that an entity’s main or most significant antagonistic or opposing activity occurs within a specified realm or domain.
-
D.
primaryEnemyForces
Indicates that the related entities constitute the main opposing or hostile forces in a conflict or competitive situation.
-
E.
antagonistOf
Indicates a relationship where one entity actively opposes, conflicts with, or serves as an adversary to another.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e172b48b308190bc430b2308cbc75b |
completed | April 16, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69e142cf5c548190a931f7b58144cd31 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:52 a.m.