Triple
T6228037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kalinga |
E139282
|
entity |
| Predicate | warCasualtiesHigh |
P1399
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Kalinga, warCasualtiesHigh, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: warCasualtiesHigh Context triple: [Kalinga, warCasualtiesHigh, true]
-
A.
warDamage
Indicates damage that was caused as a direct consequence of war or armed conflict.
-
B.
nativeCasualties
Indicates that native or indigenous people suffered deaths or injuries as a result of a particular event, action, or conflict.
-
C.
militaryCasualtiesEstimate
Indicates an estimated number of people killed, wounded, or missing as a result of military conflict or operations.
-
D.
casualties
chosen
Indicates that an event, action, or situation resulted in people being killed or injured.
-
E.
casualtiesImpact
Indicates how the number or severity of casualties affects or influences another factor, situation, or outcome.
- 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_69c008afd3148190b71e9eaa60420dd1 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062d686b88190a0e7e38ab52e2d4a |
completed | March 22, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69c055ffdf54819086d987d646e44ff5 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:22 p.m.