Triple

T17171319
Position Surface form Disambiguated ID Type / Status
Subject Take What You Got E416739 entity
Predicate associatedWithCharacter P1481 FINISHED
Object Lauren
Lauren is a character featured in the song "Take What You Got."
E1255851 NE FINISHED

How this triple was built (4 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: [Take What You Got, associatedWithCharacter, Lauren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lauren
Context triple: [Take What You Got, associatedWithCharacter, Lauren]
  • A. 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.
  • B. Lauren
    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.
  • C. Lauren
    Lauren is a common given name used for people of any gender in various English-speaking and other countries.
  • 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. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lauren
Triple: [Take What You Got, associatedWithCharacter, Lauren]
Generated description
Lauren is a character featured in the song "Take What You Got."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lauren
Target entity description: Lauren is a character featured in the song "Take What You Got."
  • A. 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.
  • B. Lauren
    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.
  • C. Lauren
    Lauren is a common given name used for people of any gender in various English-speaking and other countries.
  • 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. chosen

Provenance (5 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_6a015fc83984819098c98b75cf021e3a completed May 11, 2026, 4:49 a.m.
NEDg Description generation batch_6a0160beb4188190b6e9a91f50b6e276 completed May 11, 2026, 4:53 a.m.
NED2 Entity disambiguation (via description) batch_6a016158b1d081909b62cf73e14b3e78 completed May 11, 2026, 4:55 a.m.
Created at: April 10, 2026, 5:37 a.m.