Triple
T9943433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luque, Paraguay |
E194139
|
entity |
| Predicate | hasMunicipalLeaderTitle |
P36552
|
FINISHED |
| Object | intendente municipal |
—
|
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: intendente municipal | Statement: [Luque, Paraguay, hasMunicipalLeaderTitle, intendente municipal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMunicipalLeaderTitle Context triple: [Luque, Paraguay, hasMunicipalLeaderTitle, intendente municipal]
-
A.
hasDeputyLeaderTitle
Indicates that an entity holds a specific title associated with the role of deputy leader.
-
B.
hasMinisterTitle
Indicates that an entity holds or is associated with a specific ministerial title or office.
-
C.
civilianLeaderTitle
Indicates the official title held by a person who serves as the civilian leader of a group, organization, or jurisdiction.
-
D.
hasRepresentativeTitle
Indicates that an entity holds a formal title or designation that serves as its primary or most commonly used label or name.
-
E.
hasExecutiveHeadTitle
chosen
Indicates the official job title held by the person who serves as the executive head of an organization or 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_69ca82e409348190a393777356b80a2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb6124a188190b41feadb7b2f8922 |
completed | April 2, 2026, 12:19 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9428cc81909b4b4938566d78a7 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:45 p.m.