Triple

T37135714
Position Surface form Disambiguated ID Type / Status
Subject Cindy Campbell E919956 entity
Predicate relationshipTypeWithGeorgeLogan P205748 FINISHED
Object love interest (Scary Movie 3) 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: love interest (Scary Movie 3) | Statement: [Cindy Campbell, relationshipTypeWithGeorgeLogan, love interest (Scary Movie 3)]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithGeorgeLogan
Context triple: [Cindy Campbell, relationshipTypeWithGeorgeLogan, love interest (Scary Movie 3)]
  • A. relationshipToGeorgeCooperSr
    Indicates the specific familial or personal relationship an entity has to George Cooper Sr.
  • B. relationshipToGeorgeWilson
    Indicates the specific nature of the relationship or connection that an entity has to George Wilson.
  • C. relationshipToGeorgePage
    Indicates the specific familial, social, or professional relationship that an entity has to George Page.
  • D. relationshipToGeorgeCooperJr
    Indicates a familial or personal connection that an entity has to George Cooper Jr.
  • E. relationshipToGeorgeDeever
    Indicates the specific familial, romantic, or social connection that one entity has to George Deever.
  • F. None of above. chosen

Provenance (4 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_69f76e9e9d008190a250b0387c992c74 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_6a037cad051c8190b28b354b89208574 completed May 12, 2026, 7:17 p.m.
PD Predicate disambiguation batch_6a037a11efc08190bb7cacc1325b4dc6 completed May 12, 2026, 7:05 p.m.
PDg Predicate description generation batch_6a037c842b2c819082f1d2db995ac2eb completed May 12, 2026, 7:16 p.m.
Created at: May 3, 2026, 4:15 p.m.