Triple

T35549261
Position Surface form Disambiguated ID Type / Status
Subject State Bar of Arizona E1027307 entity
Predicate hasDivision P35 FINISHED
Object Attorney Discipline Unit
The Attorney Discipline Unit is a division of the State Bar of Arizona responsible for investigating and prosecuting ethical and professional misconduct by licensed attorneys in the state.
E2145711 NE 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 Discipline Unit | Statement: [State Bar of Arizona, hasDivision, Attorney Discipline Unit]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Attorney Discipline Unit
Triple: [State Bar of Arizona, hasDivision, Attorney Discipline Unit]
Generated description
The Attorney Discipline Unit is a division of the State Bar of Arizona responsible for investigating and prosecuting ethical and professional misconduct by licensed attorneys in the state.

Provenance (5 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_69f76e014fd481909e9f04ac603a2aa9 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79839bf9c8190904f53dd5333d269 completed May 3, 2026, 6:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3852f0f86081909d419d044fed2d5c completed June 21, 2026, 9:09 p.m.
NEDg Description generation batch_6a38545a48a881909970b888d152b021 completed June 21, 2026, 9:15 p.m.
NED2 Entity disambiguation (via description) batch_6a3854ee0cc08190a542392edeedb715 completed June 21, 2026, 9:17 p.m.
Created at: May 3, 2026, 4:04 p.m.