Triple
T1761454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Cannae |
E38666
|
entity |
| Predicate | RomanCasualties |
P6773
|
FINISHED |
| Object | tens of thousands killed |
—
|
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: tens of thousands killed | Statement: [Battle of Cannae, RomanCasualties, tens of thousands killed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: RomanCasualties Context triple: [Battle of Cannae, RomanCasualties, tens of thousands killed]
-
A.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
-
B.
RomanRepresentative
Indicates that one entity serves as an official representative or agent of the Roman state, authority, or interests in relation to another entity.
-
C.
militaryCasualtiesEstimate
chosen
Indicates an estimated number of people killed, wounded, or missing as a result of military conflict or operations.
-
D.
FrenchCasualties
Indicates that the relationship specifies the number or extent of casualties suffered by French forces in a given event or context.
-
E.
UScasualties
Indicates the number or occurrence of casualties suffered by the United States in a given conflict, event, 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_69a8862d562481908d7025a1c1f67c0d |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab173936b4819097332ee185996bbd |
completed | March 6, 2026, 6:04 p.m. |
| PD | Predicate disambiguation | batch_69aa61c9e06c819085489e00cfe72153 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.