Triple
T23591712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eliezer Ramos Parés |
E582496
|
entity |
| Predicate | sectorOfOffice |
P152836
|
FINISHED |
| Object | education |
—
|
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: education | Statement: [Eliezer Ramos Parés, sectorOfOffice, education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sectorOfOffice Context triple: [Eliezer Ramos Parés, sectorOfOffice, education]
-
A.
sectorOfGovernedEntity
Indicates the economic or administrative sector to which a governed entity (such as a jurisdiction or organization under governance) belongs.
-
B.
typeOfOffice
Indicates the specific category or kind of office that an office entity belongs to (e.g., executive, legislative, judicial, or other office types).
-
C.
typeOfMinistry
Indicates the specific category or kind of ministry that an entity belongs to or represents.
-
D.
methodOfMinistry
Indicates the specific way or approach through which ministry or religious service is carried out.
-
E.
natureOfOffice
Indicates the type or character of an office or position, specifying what kind of role or function it represents.
- 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_69e248f9e0a08190814772847003b1ff |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b035a5d88190bd2e1fa0170045cd |
completed | April 29, 2026, 7:16 a.m. |
| PD | Predicate disambiguation | batch_69f118c96a0081908a8ac98ef7e7e60c |
completed | April 28, 2026, 8:30 p.m. |
| PDg | Predicate description generation | batch_69f121cc494081908c987adfcde89b0e |
completed | April 28, 2026, 9:08 p.m. |
Created at: April 17, 2026, 6:42 p.m.