Triple

T11973660
Position Surface form Disambiguated ID Type / Status
Subject Anne Louvet E284982 entity
Predicate romanticPartnerMaritalStatus P20884 FINISHED
Object married 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: married | Statement: [Anne Louvet, romanticPartnerMaritalStatus, married]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: romanticPartnerMaritalStatus
Context triple: [Anne Louvet, romanticPartnerMaritalStatus, married]
  • A. romanticRelationshipStatus
    Indicates the nature or state of a romantic relationship between entities, such as whether they are dating, committed, separated, or otherwise romantically involved.
  • B. spouseStatus
    Indicates the marital relationship status between two individuals, such as whether they are currently spouses, formerly spouses, or not married to each other.
  • C. marital status chosen
    Indicates the legal or social state of a person’s marriage-related relationship, such as being single, married, divorced, or widowed.
  • D. unmarriedPartner
    Indicates a relationship where one person is a romantic or domestic partner of another, and they are not legally married to each other.
  • E. spouseStatusAtMarriage
    Indicates the marital status each partner held at the time their marriage to one another was formed.
  • 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_69d6ab2eaeb881909f7914758f859413 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9039107e48190ae4c4efd6257dd3c completed April 10, 2026, 2:05 p.m.
PD Predicate disambiguation batch_69d8bb40f30c8190a0e0719bd67542bf completed April 10, 2026, 8:56 a.m.
Created at: April 8, 2026, 9:46 p.m.