Triple
T29879689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Angamos |
E758841
|
entity |
| Predicate | combatantCommanderForPeru |
P77972
|
FINISHED |
| Object | Miguel Grau Seminario |
—
|
NE NERFINISHED |
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: Miguel Grau Seminario | Statement: [Battle of Angamos, combatantCommanderForPeru, Miguel Grau Seminario]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: combatantCommanderForPeru Context triple: [Battle of Angamos, combatantCommanderForPeru, Miguel Grau Seminario]
-
A.
commanderForPeru
chosen
Indicates that an entity serves or has served as a military commander on behalf of Peru.
-
B.
commandingOfficerForGranColombia
Indicates that one entity serves as the commanding officer responsible for the military forces of Gran Colombia in relation to the other entity.
-
C.
combatant2Commander
Indicates that a combatant serves under the authority or command of a specific commander.
-
D.
militaryCommanderMexican
Indicates that one entity serves as the military commander of the other entity, specifically within a Mexican military context.
-
E.
commanderArgentina
Indicates that one entity serves as the military or organizational commander of Argentina.
- 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_69f2245de2f48190a481404896b56254 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f68f670b608190a0b6ab60d722b4e0 |
completed | May 2, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69f68b7b03488190b1db5fde4c7dd6e5 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 5:57 p.m.