Triple

T20440081
Position Surface form Disambiguated ID Type / Status
Subject Nicole Parker E501360 entity
Predicate hasGivenName P17 FINISHED
Object Nicole
Nicole is a feminine given name of Greek origin, commonly used in many English- and French-speaking countries.
 E476645 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: Nicole | Statement: [Nicole Parker, hasGivenName, Nicole]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nicole
Context triple: [Nicole Parker, hasGivenName, Nicole]
  • A. Nicole
    Nicole is a central character in Margaret Atwood's dystopian novel "The Testaments," whose story helps expose and challenge the oppressive regime of Gilead.
  • B. Nicole
    Nicole is a fictional character from the American sitcom "The Gregory Hines Show."
  • C. Nicole
    Nicole is a fictional character played by English actress Kelly Reilly, known from her work in film and television dramas.
  • D. Nicole
    Nicole is a fictional character portrayed by Canadian actress Lindy Booth.
  • E. Nicole
    Nicole is a central female character in François Truffaut’s 1964 French New Wave film "The Soft Skin," involved in a clandestine love affair that drives the movie’s dramatic tension.
  • 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: Nicole
Triple: [Nicole Parker, hasGivenName, Nicole]
Generated description
Nicole is a feminine given name of Greek origin, commonly used in many English- and French-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nicole
Target entity description: Nicole is a feminine given name of Greek origin, commonly used in many English- and French-speaking countries.
  • A. Nicole chosen
    Nicole is a feminine given name of Greek origin meaning "victory of the people," commonly used in many English- and French-speaking countries.
  • B. Nicole
    Nicole is a fictional character played by English actress Kelly Reilly, known from her work in film and television dramas.
  • C. Nicole
    Nicole is a central female character in François Truffaut’s 1964 French New Wave film "The Soft Skin," involved in a clandestine love affair that drives the movie’s dramatic tension.
  • D. Nicole
    Nicole is a fictional character portrayed by Canadian actress Lindy Booth.
  • E. Nicole
    Nicole is a sharp-tongued, down-to-earth maid in Molière’s comedy "Le Bourgeois gentilhomme," often serving as a voice of reason and satire against her master’s pretensions.
  • F. None of above.

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_69e0b4ab3cfc8190ac9bf32e932316b1 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e685f20fe08190b9370b523a20153d completed April 20, 2026, 8 p.m.
NED1 Entity disambiguation (via context triple) batch_6a088b09c8988190b81fe0678c8d071b completed May 16, 2026, 3:19 p.m.
NEDg Description generation batch_6a088b7ed7188190b6defb96896bd0bc completed May 16, 2026, 3:21 p.m.
NED2 Entity disambiguation (via description) batch_6a088bda586481909f0dad34055889ee completed May 16, 2026, 3:23 p.m.
Created at: April 16, 2026, 11:31 a.m.