Triple
T34815840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | America's Mayor |
E1003633
|
entity |
| Predicate | linkedToPersonOccupation |
P2374
|
FINISHED |
| Object | lawyer |
—
|
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: lawyer | Statement: [America's Mayor, linkedToPersonOccupation, lawyer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedToPersonOccupation Context triple: [America's Mayor, linkedToPersonOccupation, lawyer]
-
A.
occupationOfAssociatedPerson
Indicates the job or professional role held by a person who is associated with another referenced entity.
-
B.
involvedOccupationOf
Indicates that an entity participates in or is associated with a particular occupation or professional role.
-
C.
recognizedOccupationOf
Indicates that one entity is acknowledged or officially accepted as the occupation or professional role held by another entity.
-
D.
associatedWithCareerOf
Indicates a relationship where something is connected or relevant to a person’s professional life, occupation, or career trajectory.
-
E.
subjectOccupation
chosen
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
- 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_69f76db717088190811b4e744610f37d |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fe610e1f6881908f10070ba64643cf |
completed | May 8, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69fe604c6c008190ad659e9b9fa82f7b |
completed | May 8, 2026, 10:14 p.m. |
Created at: May 3, 2026, 3:59 p.m.