Triple
T25481333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alcalde de Las Palmas de Gran Canaria |
E638582
|
entity |
| Predicate | officeNameInSpanish |
P170933
|
FINISHED |
| Object | Alcalde de Las Palmas de Gran Canaria |
—
|
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: Alcalde de Las Palmas de Gran Canaria | Statement: [Alcalde de Las Palmas de Gran Canaria, officeNameInSpanish, Alcalde de Las Palmas de Gran Canaria]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeNameInSpanish Context triple: [Alcalde de Las Palmas de Gran Canaria, officeNameInSpanish, Alcalde de Las Palmas de Gran Canaria]
-
A.
officeNameInPortuguese
Indicates the name or title of an office as expressed in the Portuguese language.
-
B.
officeName
Indicates the official name assigned to an office or workplace.
-
C.
officeNameInFrench
Indicates the French-language name or label used for a particular office or official position.
-
D.
officeNameInDutch
Indicates the Dutch-language name or title used for a particular office, position, or role.
-
E.
officeNameInOfficialLanguage
Indicates that an office’s title or name is given specifically in the official language of the relevant jurisdiction or organization.
- 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_69e75dbabeac8190bab30628f8b799d4 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f6984bb55c8190862eb8796868d188 |
completed | May 3, 2026, 12:35 a.m. |
| PD | Predicate disambiguation | batch_69f69661e6ec8190948251c7516a32ad |
completed | May 3, 2026, 12:27 a.m. |
| PDg | Predicate description generation | batch_69f6978ec27c8190a488e1f9c2566d38 |
completed | May 3, 2026, 12:32 a.m. |
Created at: April 21, 2026, 2:31 p.m.