Triple
T628683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation Telic |
E15876
|
entity |
| Predicate | peakTroopDeployment |
P17244
|
FINISHED |
| Object | approximately 46,000 British personnel |
—
|
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 46,000 British personnel | Statement: [Operation Telic, peakTroopDeployment, approximately 46,000 British personnel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: peakTroopDeployment Context triple: [Operation Telic, peakTroopDeployment, approximately 46,000 British personnel]
-
A.
suppliedTroopsTo
Indicates that one entity provided military personnel or forces to another entity.
-
B.
typeOfTroops
Indicates the specific category or kind of military forces involved in or associated with an entity or event.
-
C.
turretCrew
Indicates that an entity serves as a crew member operating or manning a turret associated with another entity.
-
D.
fleetStrategy
Indicates the overarching plan or approach governing how a group of vehicles or vessels is organized, deployed, and operated to achieve specific objectives.
-
E.
groundForces
Indicates that one entity deploys, commands, or involves military forces operating on land in relation to another entity or context.
- 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e5b5a308190a62165f9275e2f5f |
completed | March 1, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69a49d01b29081908be87e4cd7726ff1 |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49defe58c8190bd39ef47c9f660a7 |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:35 p.m.