Triple

T30680554
Position Surface form Disambiguated ID Type / Status
Subject Charles Eugene Flandrau E781038 entity
Predicate legalProfessionIn P196500 FINISHED
Object Minnesota NE NERFINISHED

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: Minnesota | Statement: [Charles Eugene Flandrau, legalProfessionIn, Minnesota]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: legalProfessionIn
Context triple: [Charles Eugene Flandrau, legalProfessionIn, Minnesota]
  • A. legalProfessionIncludes
    Indicates that a legal profession or role encompasses, involves, or includes another specified legal function, specialization, or activity.
  • B. legalProfessionType
    Indicates the specific category or type of legal profession associated with an entity (such as lawyer, judge, or notary).
  • C. legalProfessionRole
    Indicates that one entity holds or performs a specific professional role within the legal domain in relation to another entity or context.
  • D. legalProfessionTypeRegulated
    Indicates that the specified type of legal profession is subject to formal regulation or oversight by an authority.
  • E. legalCareerType
    Indicates the specific category or nature of a person’s professional role or trajectory within the legal field.
  • 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_69f224a92f54819095499b4d32bd5134 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69fe59d11e9881909d2f33b7c717030e completed May 8, 2026, 9:46 p.m.
PD Predicate disambiguation batch_69fe394fdfbc8190a931926ae3635cbf completed May 8, 2026, 7:28 p.m.
PDg Predicate description generation batch_69fe59d03a648190bbe846cb5730a477 completed May 8, 2026, 9:46 p.m.
Created at: April 29, 2026, 8:32 p.m.