Triple
T35064558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gökdepe |
E1011690
|
entity |
| Predicate | battleCasualtiesSide |
P82956
|
FINISHED |
| Object | heavy Turkmen casualties |
—
|
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: heavy Turkmen casualties | Statement: [Gökdepe, battleCasualtiesSide, heavy Turkmen casualties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: battleCasualtiesSide Context triple: [Gökdepe, battleCasualtiesSide, heavy Turkmen casualties]
-
A.
militaryCasualtiesSide
chosen
Indicates the side or party in a conflict to which the recorded military casualties belong.
-
B.
coalitionCasualties
Indicates that members of a coalition have suffered deaths or injuries as a result of a particular conflict, event, or action.
-
C.
battleCasualty
Indicates that an entity was killed, wounded, or otherwise harmed as a direct result of a specific battle or armed conflict.
-
D.
casualtiesCountry
Indicates that the specified country is the one in which the recorded casualties (deaths or injuries) occurred or to which those casualties belong.
-
E.
nativeCasualties
Indicates that native or indigenous people suffered deaths or injuries as a result of a particular event, action, or conflict.
- 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_69f76dd09c308190a523454853ce842b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78611cef081908cf99c196df5b068 |
completed | May 3, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69f7841812f081909d878955d114088e |
completed | May 3, 2026, 5:21 p.m. |
Created at: May 3, 2026, 4:01 p.m.