Triple
T24134128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Speyerbach |
E598034
|
entity |
| Predicate | outcomeForFrenchForces |
P154968
|
FINISHED |
| Object | victory |
—
|
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: victory | Statement: [Battle of Speyerbach, outcomeForFrenchForces, victory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: outcomeForFrenchForces Context triple: [Battle of Speyerbach, outcomeForFrenchForces, victory]
-
A.
sideOutcomeForFrenchUnion
Indicates a secondary or indirect result that occurs specifically in relation to the French Union.
-
B.
frenchTroopsEvacuated
Indicates that French military forces withdrew or were removed from a particular location or situation.
-
C.
FrenchOutcome
Indicates that an event, action, or process results in an outcome that is specifically French in nature, context, or origin.
-
D.
FrenchCasualties
Indicates that the relationship specifies the number or extent of casualties suffered by French forces in a given event or context.
-
E.
involvedFrenchTroops
Indicates that the event, action, or situation included the participation or presence of French military forces.
- F. None of above. chosen
Provenance (4 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_69e288c92e448190ac57034fa0c863ce |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1df7b6e9c819097fb546efa35821b |
completed | April 29, 2026, 10:37 a.m. |
| PD | Predicate disambiguation | batch_69f1765650fc8190a6bc1eb512b240bf |
completed | April 29, 2026, 3:09 a.m. |
| PDg | Predicate description generation | batch_69f17c28b684819084eea522126463f8 |
completed | April 29, 2026, 3:34 a.m. |
Created at: April 17, 2026, 11:26 p.m.