Triple
T5173167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gonzalo Queipo de Llano |
E116732
|
entity |
| Predicate | roleInCoup |
P50317
|
FINISHED |
| Object | leader of the uprising in Seville |
—
|
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: leader of the uprising in Seville | Statement: [Gonzalo Queipo de Llano, roleInCoup, leader of the uprising in Seville]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInCoup Context triple: [Gonzalo Queipo de Llano, roleInCoup, leader of the uprising in Seville]
-
A.
roleInMutiny
Indicates that one entity participated in a mutiny with a specific role or capacity in that rebellious action.
-
B.
coupLeader
chosen
Indicates that the subject is the primary organizer or head figure responsible for leading a coup against an existing authority.
-
C.
roleInRepublic
Indicates that an entity holds or plays a specific role or function within a republic or republican system.
-
D.
playsInRole
Indicates that an entity performs or appears in a specific role within a production, event, or context.
-
E.
roleInDialogue
Indicates that an entity participates in a dialogue with a specific conversational role (e.g., speaker, listener, moderator) relative to other participants.
- 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_69bd445ff97c81909a2615cc56235470 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd796f7c308190a721e33aabd499ac |
completed | March 20, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69bd77b529948190b86671ebe43f4734 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:45 p.m.