Triple
T2533493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | José de la Riva-Agüero |
E56216
|
entity |
| Predicate | notableOfficeSequence |
P2953
|
FINISHED |
| Object | first President of Peru |
—
|
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: first President of Peru | Statement: [José de la Riva-Agüero, notableOfficeSequence, first President of Peru]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableOfficeSequence Context triple: [José de la Riva-Agüero, notableOfficeSequence, first President of Peru]
-
A.
notableOfficeStartContext
Indicates the contextual circumstances or conditions (such as time, place, or situation) surrounding the beginning of a notable office or position held by an entity.
-
B.
notableSection
Indicates that a particular part or segment of something is especially important, prominent, or worthy of attention within the whole.
-
C.
notableElement
Indicates that an entity has a component, feature, or part that is especially significant, prominent, or noteworthy in relation to it.
-
D.
notableSeat
Indicates that an entity holds or is associated with a seat, position, or place that is considered notable or significant in some context.
-
E.
ordinalInOffice
chosen
Indicates the numerical order or rank of an individual’s term or tenure in a particular office or position.
- 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_69ab4a49b6508190bc467fbef4bac334 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd64a2194819097c66cbeb37fe859 |
completed | March 7, 2026, 7:39 a.m. |
| PD | Predicate disambiguation | batch_69abd0c4a5dc819097812db50443420a |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:47 p.m.