Triple

T32553939
Position Surface form Disambiguated ID Type / Status
Subject Vanessa "Van" Keefer E832045 entity
Predicate relationshipStatusWithEarn P198916 FINISHED
Object on-and-off girlfriend 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: on-and-off girlfriend | Statement: [Vanessa "Van" Keefer, relationshipStatusWithEarn, on-and-off girlfriend]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: relationshipStatusWithEarn
Context triple: [Vanessa "Van" Keefer, relationshipStatusWithEarn, on-and-off girlfriend]
  • A. employerRelationship
    Indicates a relationship in which one entity acts as the employer of another, having authority to hire, direct, and compensate the other party for work performed.
  • B. relationshipStatusWithNP chosen
    Indicates the type or state of a relationship that one entity has with a specified noun phrase (NP).
  • C. earningsStatus
    Indicates the current state or condition of an entity’s earnings, such as whether they are realized, projected, stable, increasing, or decreasing.
  • D. employerStatus
    Indicates the current employment relationship or condition between an employer and a worker, such as whether the person is actively employed, terminated, retired, or on leave.
  • E. earnerType
    Indicates the category or role that characterizes how an entity earns income or compensation.
  • 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_69f34926b9848190ace47d2dd0a0de7c completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_6a037c894b488190bcbec2eccaff4a01 completed May 12, 2026, 7:16 p.m.
PD Predicate disambiguation batch_6a0379edf2d88190b492fca86ed23cac completed May 12, 2026, 7:05 p.m.
Created at: May 1, 2026, 1:02 a.m.