Triple
T9833391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jaime Lerner |
E239040
|
entity |
| Predicate | numberOfTermsAsMayorOfCuritiba |
P31629
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Jaime Lerner, numberOfTermsAsMayorOfCuritiba, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTermsAsMayorOfCuritiba Context triple: [Jaime Lerner, numberOfTermsAsMayorOfCuritiba, 3]
-
A.
numberOfTermsAsMayor
chosen
Indicates the number of distinct terms an individual has served in the role of mayor.
-
B.
hasMayorTerm
Indicates that a specified individual holds or has held the office of mayor for a particular jurisdiction during a defined term.
-
C.
numberOfTermsAsMayorOfAtlanta
Indicates the number of separate terms an individual has served as mayor of Atlanta.
-
D.
hasMayor
Indicates that one entity serves as the mayor of another entity, typically a city, town, or municipality.
-
E.
wonMayoraltyOf
Indicates that one entity won the election to become mayor of a specified place or jurisdiction.
- 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_69ca84e314108190978324a4bdb959f8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb336bfc4819084f0d4d6d1867484 |
completed | April 2, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69cd03e30bc08190816c0a6d29c21b0f |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:32 p.m.