Triple

T37488057
Position Surface form Disambiguated ID Type / Status
Subject Lena Goldman E931586 entity
Predicate spousePoliticalActivityLocation P197967 FINISHED
Object New Jersey 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: New Jersey | Statement: [Lena Goldman, spousePoliticalActivityLocation, New Jersey]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: spousePoliticalActivityLocation
Context triple: [Lena Goldman, spousePoliticalActivityLocation, New Jersey]
  • A. spousePoliticalActivity
    Indicates that one person’s spouse engages in political actions, involvement, or advocacy connected to that person or their role.
  • B. spousePoliticalMovement
    Indicates that the political movement is one with which the spouse of the subject is affiliated or identified.
  • C. spouseOffice
    Indicates that one entity holds an office or position that is associated with, or held by, the spouse of another entity.
  • D. spousePoliticalBase
    Indicates that one person’s political support or influence is primarily derived from, or strongly associated with, their spouse’s political base or constituency.
  • E. spouseOfOfficeHolderJurisdiction
    Indicates that one person is the spouse of a public office holder, with the relationship specifically tied to the jurisdiction in which that office is held.
  • 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_69f76ec382248190b47844df596123c6 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69febce5877c8190a5e000ef5331ec88 completed May 9, 2026, 4:49 a.m.
PD Predicate disambiguation batch_69febad1cd588190abc7686bcb39a371 completed May 9, 2026, 4:40 a.m.
PDg Predicate description generation batch_69febce420b081908e1c052751a22b1f completed May 9, 2026, 4:49 a.m.
Created at: May 3, 2026, 4:17 p.m.