Triple

T30925822
Position Surface form Disambiguated ID Type / Status
Subject Hot Girl (The Office U.S.) E787850 entity
Predicate featuresRelationshipDevelopment P87667 FINISHED
Object Jim Halpert and Pam Beesly 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 Pam Beesly | Statement: [Hot Girl (The Office U.S.), featuresRelationshipDevelopment, Jim Halpert and Pam Beesly]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: featuresRelationshipDevelopment
Context triple: [Hot Girl (The Office U.S.), featuresRelationshipDevelopment, Jim Halpert and Pam Beesly]
  • A. relationshipDevelopsWith chosen
    Indicates that a relationship grows, evolves, or becomes more developed between two entities over time.
  • B. coversRelationship
    Indicates that one entity extends over, includes, or provides encompassing coverage for another entity or set of entities.
  • C. developmentLinkedTo
    Indicates that the development or progression of one entity is causally or contextually connected to the development or progression of another entity.
  • D. exploresRelationship
    Indicates that one entity actively investigates, examines, or probes the nature, dynamics, or implications of its relationship with another entity.
  • E. relationshipFocus
    Indicates a relationship where particular attention, priority, or emphasis is placed on the connection between two or more 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_69f224bfaca88190b9d0dfcc86297fe9 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_6a0042524d8c8190884a10fce669ae95 completed May 10, 2026, 8:31 a.m.
PD Predicate disambiguation batch_6a0041e89bd881909e32764699bcb89b completed May 10, 2026, 8:29 a.m.
Created at: April 29, 2026, 8:51 p.m.