Triple
T31723668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golpe de Estado de 1955 en Argentina |
E809650
|
entity |
| Predicate | derrocaCargo |
P172893
|
FINISHED |
| Object | Presidente de la Nación Argentina |
—
|
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: Presidente de la Nación Argentina | Statement: [Golpe de Estado de 1955 en Argentina, derrocaCargo, Presidente de la Nación Argentina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: derrocaCargo Context triple: [Golpe de Estado de 1955 en Argentina, derrocaCargo, Presidente de la Nación Argentina]
-
A.
cargoLoading
Indicates the action or process of placing cargo onto a vehicle, vessel, or other transport medium for shipment or movement.
-
B.
railDisasterCargo
Indicates a rail transport accident or disaster specifically involving cargo or freight.
-
C.
mainCargo
Indicates that one entity serves as the primary or principal cargo carried or transported by another entity.
-
D.
cargoSystem
Indicates a relationship where an entity is part of, managed by, or associated with a cargo-handling or cargo-management system.
-
E.
cargoVehicle
Indicates a relationship where a vehicle is used or designated for transporting cargo or goods.
- 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_69f348e009c8819095d77df52c645b9c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6b0d21dd08190a9883ff71c94c71c |
completed | May 3, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69f6aca3dedc81908b519d53d2909868 |
completed | May 3, 2026, 2:02 a.m. |
| PDg | Predicate description generation | batch_69f6afeaaef88190aefa97e83f8db906 |
completed | May 3, 2026, 2:16 a.m. |
Created at: April 30, 2026, 11:19 p.m.