Triple

T8213615
Position Surface form Disambiguated ID Type / Status
Subject Betsy Gotbaum E191880 entity
Predicate notableOfficeScope P7602 FINISHED
Object oversight of New York City agencies 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: oversight of New York City agencies | Statement: [Betsy Gotbaum, notableOfficeScope, oversight of New York City agencies]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: notableOfficeScope
Context triple: [Betsy Gotbaum, notableOfficeScope, oversight of New York City agencies]
  • A. notableOfficeStartContext
    Indicates the contextual circumstances or conditions (such as time, place, or situation) surrounding the beginning of a notable office or position held by an entity.
  • B. officeScope chosen
    Indicates that a relationship, authority, or action is limited to, defined within, or applicable only in the context of a particular office or official position.
  • C. notableOfficeStatus
    Indicates that an entity holds or has held a particularly significant or distinguished official position or office.
  • D. notabilityScope
    Indicates the domain, field, or context within which something is considered notable or significant.
  • E. includedOffice
    Indicates that one office is contained within, or forms part of, another office or organizational unit.
  • 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_69ca82c8c054819087fedd9a5436b8a3 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb76e1ffa081908883338e7d3a7c6d completed March 31, 2026, 7:25 a.m.
PD Predicate disambiguation batch_69cb36ad01ac81909609b15f6a6c8581 completed March 31, 2026, 2:51 a.m.
Created at: March 30, 2026, 5:44 p.m.