Triple

T15675475
Position Surface form Disambiguated ID Type / Status
Subject Jon Arbuckle E377430 entity
Predicate canonicalRelationshipStatus P82370 FINISHED
Object dating Liz Wilson in later strips 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: dating Liz Wilson in later strips | Statement: [Jon Arbuckle, canonicalRelationshipStatus, dating Liz Wilson in later strips]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: canonicalRelationshipStatus
Context triple: [Jon Arbuckle, canonicalRelationshipStatus, dating Liz Wilson in later strips]
  • A. relationshipStatusInStory
    Indicates the type or state of the relationship between entities as it exists within the context of a specific story or narrative.
  • B. companionshipStatus
    Indicates the current state or condition of a relationship of companionship between two or more entities.
  • C. romanticRelationshipStatus chosen
    Indicates the nature or state of a romantic relationship between entities, such as whether they are dating, committed, separated, or otherwise romantically involved.
  • D. inRelationshipWith
    Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
  • E. relationshipStatusDuringFilm
    Indicates the type or state of a relationship between entities specifically during the time period in which a film takes place or is produced.
  • 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_69d85cd2e28481909d4e975bee20872f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f2c996c8190a9ebe0e92608feaa completed April 16, 2026, 2:53 a.m.
PD Predicate disambiguation batch_69deda8b36a4819081cb5708fe77ef51 completed April 15, 2026, 12:23 a.m.
Created at: April 10, 2026, 4:16 a.m.