Triple
T1894617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation Power Pack |
E41949
|
entity |
| Predicate | troopStrength |
P6153
|
FINISHED |
| Object | over 20,000 U.S. troops |
—
|
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: over 20,000 U.S. troops | Statement: [Operation Power Pack, troopStrength, over 20,000 U.S. troops]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: troopStrength Context triple: [Operation Power Pack, troopStrength, over 20,000 U.S. troops]
-
A.
typeOfTroops
Indicates the specific category or kind of military forces involved in or associated with an entity or event.
-
B.
combatantStrength
Indicates the relative level of power, capability, or effectiveness one combatant has in a conflict or confrontation compared to others.
-
C.
personnelStrength
Indicates the number or capacity of people assigned to or available for a particular unit, organization, or operation.
-
D.
suppliedTroopsTo
Indicates that one entity provided military personnel or forces to another entity.
-
E.
numberOfTroopsInvolved
chosen
Indicates the quantity of military personnel participating in or assigned to a specific operation, event, or engagement.
- 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_69a8864b6de0819098d089f6a1b910a7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb16c09e48190a345c95eab59fd87 |
completed | March 7, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69abafe7e7e88190b58c0df59187c0c2 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:34 p.m.