Triple
T16894803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Dompaire |
E424269
|
entity |
| Predicate | FrenchUnitType |
P70976
|
FINISHED |
| Object | armoured division |
—
|
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: armoured division | Statement: [Battle of Dompaire, FrenchUnitType, armoured division]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: FrenchUnitType Context triple: [Battle of Dompaire, FrenchUnitType, armoured division]
-
A.
FrenchUnit
chosen
Indicates that a unit or entity is associated with France, typically by origin, affiliation, or national identity.
-
B.
FrenchOperation
Indicates an operation, mission, or activity that is conducted by, under the authority of, or primarily involving France or French entities.
-
C.
FrenchCommander
Indicates that an entity serves as a military commander associated with France.
-
D.
FrenchRole
Indicates a role or position that an entity holds specifically within a French context (e.g., in France or related to French institutions, culture, or language).
-
E.
notableMilitaryUnit
Indicates that an entity is a military unit that holds particular significance, prominence, or recognition in some context.
- 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_69d889da3e8c8190a2b118f383f0beac |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3c8d6bfc88190b6b47b89c1135871 |
completed | April 18, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69e32b90ec3c819099c51bb7baf2984c |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:29 a.m.