Triple
T2492881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cuban intervention in Angola |
E52084
|
entity |
| Predicate | numberOfTroops |
P6153
|
FINISHED |
| Object | over 30000 Cuban troops at peak |
—
|
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 30000 Cuban troops at peak | Statement: [Cuban intervention in Angola, numberOfTroops, over 30000 Cuban troops at peak]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTroops Context triple: [Cuban intervention in Angola, numberOfTroops, over 30000 Cuban troops at peak]
-
A.
typeOfTroops
Indicates the specific category or kind of military forces involved in or associated with an entity or event.
-
B.
numberOfTroopsInvolved
chosen
Indicates the quantity of military personnel participating in or assigned to a specific operation, event, or engagement.
-
C.
suppliedTroopsTo
Indicates that one entity provided military personnel or forces to another entity.
-
D.
combatantStrength
Indicates the relative level of power, capability, or effectiveness one combatant has in a conflict or confrontation compared to others.
-
E.
commandingForce1Strength
Indicates that one entity has a certain level or measure of strength in its role as the primary commanding force over another entity or situation.
- 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_69ab4955111c8190835bf619adec21ff |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd192cad08190b13bf8e2d7149199 |
completed | March 7, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69abd0b980b481908d4932bcea4a6167 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:45 p.m.