Triple
T1323581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Otunga |
E28274
|
entity |
| Predicate | legalOccupationStatus |
P19008
|
FINISHED |
| Object | licensed attorney (Illinois) |
—
|
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: licensed attorney (Illinois) | Statement: [David Otunga, legalOccupationStatus, licensed attorney (Illinois)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalOccupationStatus Context triple: [David Otunga, legalOccupationStatus, licensed attorney (Illinois)]
-
A.
hasProfessionalStatus
chosen
Indicates that an entity holds a particular professional standing, rank, or qualification within a field or occupation.
-
B.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
C.
careerStatus
Indicates the current stage, position, or condition of an entity within its professional or occupational life.
-
D.
legalProfessionRole
Indicates that one entity holds or performs a specific professional role within the legal domain in relation to another entity or context.
-
E.
requiredOccupationOf
Indicates that one entity specifies the occupation or job role that is required or expected for another entity (such as a position, task, or qualification).
- 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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c19caa148190a1f5be734b7d9005 |
completed | March 1, 2026, 10:45 p.m. |
| PD | Predicate disambiguation | batch_69a4beedb49c8190beb5b85cdda05013 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:55 p.m.