Triple
T13559663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Expédition d’Irlande |
E323870
|
entity |
| Predicate | nombreDeSoldatsPrévu |
P6153
|
FINISHED |
| Object | environ 14 000 soldats français |
—
|
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: environ 14 000 soldats français | Statement: [Expédition d’Irlande, nombreDeSoldatsPrévu, environ 14 000 soldats français]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nombreDeSoldatsPrévu Context triple: [Expédition d’Irlande, nombreDeSoldatsPrévu, environ 14 000 soldats français]
-
A.
soldiersCapacity
Indicates the maximum number of soldiers that an entity can hold, support, or accommodate.
-
B.
typeOfTroops
Indicates the specific category or kind of military forces involved in or associated with an entity or event.
-
C.
numberOfTroopsInvolved
chosen
Indicates the quantity of military personnel participating in or assigned to a specific operation, event, or engagement.
-
D.
suppliedTroopsTo
Indicates that one entity provided military personnel or forces to another entity.
-
E.
garrisonSize
Indicates the number of troops or defenders stationed at a particular location as its garrison.
- 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_69d8076830b48190910a902bae5888e2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae13bec4819084c1770638c00ed9 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:47 p.m.