Triple

T7905184
Position Surface form Disambiguated ID Type / Status
Subject Chuck Noland E183557 entity
Predicate maritalStatusAtStart P20884 FINISHED
Object in a relationship with Kelly Frears 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: in a relationship with Kelly Frears | Statement: [Chuck Noland, maritalStatusAtStart, in a relationship with Kelly Frears]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: maritalStatusAtStart
Context triple: [Chuck Noland, maritalStatusAtStart, in a relationship with Kelly Frears]
  • A. spouseStatusAtMarriage
    Indicates the marital status each partner held at the time their marriage to one another was formed.
  • B. marital status chosen
    Indicates the legal or social state of a person’s marriage-related relationship, such as being single, married, divorced, or widowed.
  • C. spouseStatus
    Indicates the marital relationship status between two individuals, such as whether they are currently spouses, formerly spouses, or not married to each other.
  • D. marriageType
    Indicates the specific legal or social category of a marriage relationship that exists between two spouses.
  • E. maritalBasis
    Indicates that the relationship or status in question is founded on, justified by, or determined due to a marital relationship between the involved entities.
  • 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_69ca828d13088190b222be7aa9f9315c completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3a56c9f0819094dc87fe55a8823e completed March 31, 2026, 3:07 a.m.
PD Predicate disambiguation batch_69cae92f9498819085277879e59aa072 completed March 30, 2026, 9:20 p.m.
Created at: March 30, 2026, 5:03 p.m.