Triple
T13901739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York Bar |
E334239
|
entity |
| Predicate | authorizedProfession |
P23182
|
FINISHED |
| Object | attorney |
—
|
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: attorney | Statement: [New York Bar, authorizedProfession, attorney]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: authorizedProfession Context triple: [New York Bar, authorizedProfession, attorney]
-
A.
hasRegulatedProfession
Indicates that an entity practices or is associated with a profession that is formally regulated by laws, standards, or licensing authorities.
-
B.
isAssociatedWithProfessionOfBearer
Indicates that one entity is connected to, or involved with, the profession or occupational role held by another entity.
-
C.
hasProfessionalStatus
Indicates that an entity holds a particular professional standing, rank, or qualification within a field or occupation.
-
D.
professionalStatusRestriction
Indicates a limitation or condition placed on someone’s professional role, eligibility, or activities.
-
E.
recognizesProfession
chosen
Indicates that one entity acknowledges or identifies another entity’s professional role or occupation as such.
- 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_69d81c5eaa9c819083b1ff8689179565 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de25d9c7a48190ad8fb0ca676f4f7b |
completed | April 14, 2026, 11:32 a.m. |
| PD | Predicate disambiguation | batch_69dd464b1ab48190ae50bfc902bf6ef7 |
completed | April 13, 2026, 7:38 p.m. |
Created at: April 9, 2026, 10:15 p.m.