Triple
T34894461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Président de l’Assemblée Populaire Communale d’Alger |
E1006391
|
entity |
| Predicate | correspondingOfficeType |
P82633
|
FINISHED |
| Object | mayor |
—
|
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: mayor | Statement: [Président de l’Assemblée Populaire Communale d’Alger, correspondingOfficeType, mayor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correspondingOfficeType Context triple: [Président de l’Assemblée Populaire Communale d’Alger, correspondingOfficeType, mayor]
-
A.
hasOfficeType
Indicates that an entity’s office is classified as a specific type or category of office.
-
B.
governsOfficeType
Indicates that an entity has authoritative control or regulatory oversight over a particular type or category of office.
-
C.
correspondingOfficeInOtherJurisdiction
chosen
Indicates that an office has a counterpart or equivalent office in a different legal or geographic jurisdiction.
-
D.
subjectOffice
Indicates the office or official position held by the subject in relation to another entity or context.
-
E.
correspondingGovernmentOffice
Indicates that one entity is the official government office responsible for handling matters related to the other entity.
- 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_69f76dbfe5788190ad8b64f241f470c8 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78710282c81909146dc0be91e983f |
completed | May 3, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f784162134819098413482ef52042f |
completed | May 3, 2026, 5:21 p.m. |
Created at: May 3, 2026, 4 p.m.