Triple
T8616576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Ulm |
E204053
|
entity |
| Predicate | hasCapturedTroops |
P57367
|
FINISHED |
| Object | approximately 30,000 to 60,000 Austrian soldiers |
—
|
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: approximately 30,000 to 60,000 Austrian soldiers | Statement: [Battle of Ulm, hasCapturedTroops, approximately 30,000 to 60,000 Austrian soldiers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCapturedTroops Context triple: [Battle of Ulm, hasCapturedTroops, approximately 30,000 to 60,000 Austrian soldiers]
-
A.
capturedForce
chosen
Indicates that one entity has taken control of another entity or group through force, restraint, or coercive action.
-
B.
numberOfSettlersCaptured
Indicates the quantity of settlers who have been taken captive in a given context or event.
-
C.
capturedInWar
Indicates that one entity was taken prisoner or seized by another entity as a result of armed conflict or wartime actions.
-
D.
capturedOff
Indicates that one entity has taken another entity away or into custody, removing it from its original location or control.
-
E.
wasRecapturedBy
Indicates that an entity which had previously escaped or been released was caught again by another entity.
- 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_69ca832ceab8819096e4a9f546695079 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc4703b57c81909511de72fa5c38d7 |
completed | March 31, 2026, 10:13 p.m. |
| PD | Predicate disambiguation | batch_69cc455437488190b7506f820daf6e32 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:25 p.m.