Triple

T17171208
Position Surface form Disambiguated ID Type / Status
Subject Charlie Price E416736 entity
Predicate romanticInterest P7325 FINISHED
Object Lauren E421483 NE 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: Lauren | Statement: [Charlie Price, romanticInterest, Lauren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lauren
Context triple: [Charlie Price, romanticInterest, Lauren]
  • A. Lauren
    Lauren is a common given name used for people of any gender in various English-speaking and other countries.
  • B. Lauren
    Lauren is a central female protagonist in the romantic comedy film "Think Like a Man," portrayed as a successful, relationship-seeking woman whose love life is influenced by Steve Harvey’s dating advice.
  • C. Lauren chosen
    Lauren is a central character in the musical "Kinky Boots," known as a quirky, down-to-earth factory worker who becomes a key ally and love interest to the protagonist.
  • D. Lauren Lambert
    Lauren Lambert is best known as the former wife of American actor John C. McGinley.
  • E. Lauren Lane
    Lauren Lane is an American television and stage actress best known for playing the sophisticated and sarcastic C.C. Babcock on the 1990s sitcom "The Nanny."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d886d5f34c8190b24564dfaa63f3fb completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3fc097950819095631ee5679e03af completed April 18, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01483f85648190acaeb197013e1f1b completed May 11, 2026, 3:08 a.m.
Created at: April 10, 2026, 5:37 a.m.