Triple
T2541531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Washington State Bar |
E57794
|
entity |
| Predicate | hasRegulatedProfession |
P39432
|
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: [Washington State Bar, hasRegulatedProfession, lawyer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegulatedProfession Context triple: [Washington State Bar, hasRegulatedProfession, lawyer]
-
A.
regulatesProfession
Indicates that one entity has authority to control, oversee, or set rules governing the practice of a particular profession by another entity.
-
B.
hasProfessionalStatus
Indicates that an entity holds a particular professional standing, rank, or qualification within a field or occupation.
-
C.
isAssociatedWithProfessionOfBearer
Indicates that one entity is connected to, or involved with, the profession or occupational role held by another entity.
-
D.
hasProfessionalStatusRequirement
Indicates that something is subject to a condition specifying a particular professional status that must be held or met.
-
E.
recognizesProfession
Indicates that one entity acknowledges or identifies another entity’s professional role or occupation as such.
- F. None of above. chosen
Provenance (4 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_69ab4a5212d88190b989ce129f2ad87f |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd2bc7b5481908b3664495e99f1a4 |
completed | March 7, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69abd0c63964819092d5f578195ae8dd |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd1c7b6e48190be9a0c31069df797 |
completed | March 7, 2026, 7:20 a.m. |
Created at: March 6, 2026, 9:47 p.m.