Triple

T30925823
Position Surface form Disambiguated ID Type / Status
Subject Hot Girl (The Office U.S.) E787850 entity
Predicate featuresRomanticInterest P192977 FINISHED
Object Jim Halpert and Katy 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: Jim Halpert and Katy | Statement: [Hot Girl (The Office U.S.), featuresRomanticInterest, Jim Halpert and Katy]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: featuresRomanticInterest
Context triple: [Hot Girl (The Office U.S.), featuresRomanticInterest, Jim Halpert and Katy]
  • A. hasFictionalRomanticInterest chosen
    Indicates that one entity is portrayed as having a romantic attraction or interest toward another entity within a fictional context.
  • B. loveInterestPortrayedBy
    Indicates that a character’s romantic interest is depicted or played by a particular actor or performer.
  • C. formerRomanticInterest
    Indicates that one entity previously had a romantic relationship or attraction toward another entity, but that romantic connection has since ended.
  • D. loveInterestType
    Indicates the specific kind or category of romantic or affectionate relationship that exists between the related entities.
  • E. loveInterest
    Indicates that one entity is the romantic object of affection or attraction for another entity.
  • 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_69f224bfaca88190b9d0dfcc86297fe9 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_6a0045a7b4c081908e4dedabda7cf790 completed May 10, 2026, 8:45 a.m.
PD Predicate disambiguation batch_6a0042b148a48190974b173f352e4b7f completed May 10, 2026, 8:32 a.m.
Created at: April 29, 2026, 8:51 p.m.