Triple

T173435
Position Surface form Disambiguated ID Type / Status
Subject Falcon Crest E3525 entity
Predicate hasCharacter P2308 FINISHED
Object Lauren Daniels
Lauren Daniels is a fictional character from the American prime-time television soap opera "Falcon Crest."
E81259 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 Daniels | Statement: [Falcon Crest, hasCharacter, Lauren Daniels]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lauren Daniels
Context triple: [Falcon Crest, hasCharacter, Lauren Daniels]
  • A. Jessyca Wilson
    Jessyca Wilson is a songwriter best known for her work on the track "Save Room."
  • B. Erin McDermott
    Erin McDermott is a collegiate sports administrator best known as the athletic director at Harvard University.
  • C. Megan Davis
    Megan Davis is an Australian constitutional lawyer and Indigenous rights advocate renowned for her leadership in advancing Aboriginal and Torres Strait Islander peoples’ rights and constitutional recognition.
  • D. Tanita Strahan
    Tanita Strahan is an American visual artist and the eldest daughter of former NFL star and television personality Michael Strahan.
  • E. Elissa Leonard
    Elissa Leonard is an American filmmaker and producer known for her work in documentary and independent film, as well as for being married to Federal Reserve Chair Jerome H. Powell.
  • 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 Daniels
Triple: [Falcon Crest, hasCharacter, Lauren Daniels]
Generated description
Lauren Daniels is a fictional character from the American prime-time television soap opera "Falcon Crest."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lauren Daniels
Target entity description: Lauren Daniels is a fictional character from the American prime-time television soap opera "Falcon Crest."
  • A. Jessyca Wilson
    Jessyca Wilson is a songwriter best known for her work on the track "Save Room."
  • B. Erin McDermott
    Erin McDermott is a collegiate sports administrator best known as the athletic director at Harvard University.
  • C. Megan Davis
    Megan Davis is an Australian constitutional lawyer and Indigenous rights advocate renowned for her leadership in advancing Aboriginal and Torres Strait Islander peoples’ rights and constitutional recognition.
  • D. Tanita Strahan
    Tanita Strahan is an American visual artist and the eldest daughter of former NFL star and television personality Michael Strahan.
  • E. Elissa Leonard
    Elissa Leonard is an American filmmaker and producer known for her work in documentary and independent film, as well as for being married to Federal Reserve Chair Jerome H. Powell.
  • 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_69a25374990081909766d30c79a18e0e completed Feb. 28, 2026, 2:31 a.m.
NER Named-entity recognition batch_69a258e1ec008190a89dd452f72574f4 completed Feb. 28, 2026, 2:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69a58030d0e48190a6390478e62f8659 completed March 2, 2026, 12:18 p.m.
NEDg Description generation batch_69a582410b008190a4f354b354e27c31 completed March 2, 2026, 12:27 p.m.
NED2 Entity disambiguation (via description) batch_69a582eb73c08190982a7fa6bbee536f completed March 2, 2026, 12:30 p.m.
Created at: Feb. 28, 2026, 2:39 a.m.