Triple
T29397928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franco-Moroccan War (1844) |
E745552
|
entity |
| Predicate | usedByFrance |
P180242
|
FINISHED |
| Object | French Army |
—
|
NE NERFINISHED |
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: French Army | Statement: [Franco-Moroccan War (1844), usedByFrance, French Army]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedByFrance Context triple: [Franco-Moroccan War (1844), usedByFrance, French Army]
-
A.
reservedToFrance
Indicates that something is exclusively allocated or designated for France.
-
B.
strategyUsedByFrench
Indicates that a particular strategy is employed or implemented by the French.
-
C.
effectOnFrance
Indicates the impact, influence, or consequences that something has on France.
-
D.
significanceForFrance
Indicates that something holds particular importance, impact, or relevance specifically in the context of France.
-
E.
usedBeforeFrenchRevolution
Indicates that something was in use or practiced prior to the onset of the French Revolution.
- 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_69f0a79dfabc81908755382ee47791e2 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f739a638748190808e7a2930dce16e |
completed | May 3, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69f732f2dc6c8190a4e86da98cc5eb05 |
completed | May 3, 2026, 11:35 a.m. |
| PDg | Predicate description generation | batch_69f739a58b3c81908abc2b8738a65678 |
completed | May 3, 2026, 12:03 p.m. |
Created at: April 28, 2026, 2:48 p.m.