Triple
T7603175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deputy Chairperson of the African Union Commission |
E180033
|
entity |
| Predicate | titleInPortuguese |
P77724
|
FINISHED |
| Object | Vice-Presidente da Comissão da União Africana |
—
|
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: Vice-Presidente da Comissão da União Africana | Statement: [Deputy Chairperson of the African Union Commission, titleInPortuguese, Vice-Presidente da Comissão da União Africana]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleInPortuguese Context triple: [Deputy Chairperson of the African Union Commission, titleInPortuguese, Vice-Presidente da Comissão da União Africana]
-
A.
equivalentTitleInPortuguese
Indicates that one entity has a title that is the equivalent of another entity’s title, specifically in Portuguese.
-
B.
titleInSpanish
Indicates that one entity is the title of another entity expressed in the Spanish language.
-
C.
nameInPortuguese
Indicates that an entity is referred to by a specific name when expressed in the Portuguese language.
-
D.
titleInEnglish
Indicates that an entity’s title or name is given in the English language.
-
E.
titleInLatinScript
Indicates that the title of an entity is written or represented using a Latin-based writing system.
- 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_69c69f3567008190ab01d2ca7b53584a |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f9fa633081909660f653f5b073cd |
completed | March 27, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e485f88190910b39da52a955fe |
completed | March 27, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69c6f8195e5c8190835e28d44e19f6ef |
completed | March 27, 2026, 9:35 p.m. |
Created at: March 27, 2026, 3:54 p.m.