Triple
T11406939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Landen |
E270261
|
entity |
| Predicate | FrenchForcesStrength |
P24882
|
FINISHED |
| Object | approximately 80,000 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 80,000 soldiers | Statement: [Battle of Landen, FrenchForcesStrength, approximately 80,000 soldiers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: FrenchForcesStrength Context triple: [Battle of Landen, FrenchForcesStrength, approximately 80,000 soldiers]
-
A.
FrenchUnit
Indicates that a unit or entity is associated with France, typically by origin, affiliation, or national identity.
-
B.
strengthFrance
chosen
Indicates a relationship where a level, measure, or attribute of strength is associated specifically with France.
-
C.
approximateStrengthFrancoSpanish
Indicates an estimated or inferred level of strength or intensity in the relationship or interaction between Franco and Spanish entities.
-
D.
FrenchCasualties
Indicates that the relationship specifies the number or extent of casualties suffered by French forces in a given event or context.
-
E.
FrenchOperation
Indicates an operation, mission, or activity that is conducted by, under the authority of, or primarily involving France or French entities.
- 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_69d6aaddeaa8819088b30ef7b50598c9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8014c820c81908538ba4a08e13230 |
completed | April 9, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69d7e70ffd708190b62a78ebcbce9f78 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:34 p.m.