Triple
T12610435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marty Quinn |
E301101
|
entity |
| Predicate | politicalOfficeType |
P22253
|
FINISHED |
| Object | municipal office |
—
|
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: municipal office | Statement: [Marty Quinn, politicalOfficeType, municipal office]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: politicalOfficeType Context triple: [Marty Quinn, politicalOfficeType, municipal office]
-
A.
typeOfOffice
Indicates the specific category or kind of office that an office entity belongs to (e.g., executive, legislative, judicial, or other office types).
-
B.
topPoliticalOffice
Indicates that the subject holds or is associated with the highest-ranking political office within a given governmental or political system.
-
C.
typeOfPolitician
chosen
Indicates that one politician belongs to a specific category or role of political office (e.g., senator, mayor, minister) within a political system.
-
D.
electedOffice
Indicates that an entity holds or has held a particular office or position as a result of an election.
-
E.
isPoliticalOffice
Indicates that the subject is a formal governmental or political position held within a public institution or authority.
- 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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9559458dc8190bc4d6e697e99d70e |
completed | April 10, 2026, 7:55 p.m. |
| PD | Predicate disambiguation | batch_69d9541894fc8190a0c3706a414279f0 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 9, 2026, 5:11 p.m.