Triple
T30517733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | People’s Defense Forces |
E776610
|
entity |
| Predicate | hasCombatantsFrom |
P21502
|
FINISHED |
| Object | Kurdish population |
—
|
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: Kurdish population | Statement: [People’s Defense Forces, hasCombatantsFrom, Kurdish population]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCombatantsFrom Context triple: [People’s Defense Forces, hasCombatantsFrom, Kurdish population]
-
A.
combatantsIncluded
chosen
Indicates that the specified entities are participants or parties involved in a particular combat or conflict.
-
B.
hasCombatantRole
Indicates that an entity participates in a conflict or battle in a specific combat-related role or capacity.
-
C.
hasCombatantSide
Indicates a relationship where a conflict, battle, or war is associated with one of the participating sides or factions involved in the combat.
-
D.
hasEnemies
Indicates that one entity is in an antagonistic or hostile relationship with another, considering them an enemy.
-
E.
mainCombatant
Indicates that the subject is the primary participant or leading party in a conflict, battle, or combat situation involving the object.
- 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_69f2249b23c4819087fa85496d92f43f |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a016336c58081909c58c5772e6fb488 |
completed | May 11, 2026, 5:03 a.m. |
| PD | Predicate disambiguation | batch_6a0160f25d8081909a6aaa375e9850b0 |
completed | May 11, 2026, 4:54 a.m. |
Created at: April 29, 2026, 8:16 p.m.