Triple
T10196014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Domingo de Salazar |
E238162
|
entity |
| Predicate | roleInPhilippines |
P92633
|
FINISHED |
| Object | pioneer of organized diocesan structure |
—
|
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: pioneer of organized diocesan structure | Statement: [Domingo de Salazar, roleInPhilippines, pioneer of organized diocesan structure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInPhilippines Context triple: [Domingo de Salazar, roleInPhilippines, pioneer of organized diocesan structure]
-
A.
roleInPakistan
Indicates that an entity holds or has held a specific role, position, or function within the context of Pakistan.
-
B.
roleInPeru
Indicates that an entity holds or has held an official or notable role, position, or function within the country of Peru.
-
C.
roleInCanada
Indicates that one entity holds or performs a specific role, position, or function within the context of Canada.
-
D.
roleInTaiwan
Indicates that an entity holds or has held an official or notable role, position, or function within the political, administrative, or social context of Taiwan.
-
E.
roleInBrazil
Indicates that an entity holds or held a specific role, position, or function within the context of Brazil.
- 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_69ca84de1b208190bf17bb305b002605 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdedc9360081908dd73e36022a3dfd |
completed | April 2, 2026, 4:17 a.m. |
| PD | Predicate disambiguation | batch_69cd7c8477648190bc55c56aeec507d3 |
completed | April 1, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69cd7edc6cf081909d95859d880a4059 |
completed | April 1, 2026, 8:23 p.m. |
Created at: March 30, 2026, 9:13 p.m.