Triple

T16484220
Position Surface form Disambiguated ID Type / Status
Subject Luc Oursel E400396 entity
Predicate givenName P17 FINISHED
Object Luc
Luc is a masculine given name of Latin origin, commonly used in French-speaking countries as a form of "Luke."
 E216416 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: Luc | Statement: [Luc Oursel, givenName, Luc]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Luc
Context triple: [Luc Oursel, givenName, Luc]
  • A. Luc
    Luc is the given name of Luc Longley, the Australian former professional basketball player and three-time NBA champion with the Chicago Bulls.
  • B. Lou
    Lou is a supporting character in the romantic drama film "Stuck in Love," involved in the intertwined relationships and personal struggles of a family of writers.
  • C. Lou
    Lou is the central canine hero of the animated film "Cats & Dogs," leading the fight to protect humanity from a secret feline plot.
  • D. Lou
    Lou is a character in the television miniseries "The Continental: From the World of John Wick," set in the action-packed criminal underworld of the John Wick franchise.
  • E. Lou
    Lou is a character from the virtual reality co-op shooter game "After the Fall," set in a post-apocalyptic, frozen Los Angeles overrun by mutated creatures.
  • 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: Luc
Triple: [Luc Oursel, givenName, Luc]
Generated description
Luc is a masculine given name of Latin origin, commonly used in French-speaking countries as a form of "Luke."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Luc
Target entity description: Luc is a masculine given name of Latin origin, commonly used in French-speaking countries as a form of "Luke."
  • A. Luc chosen
    Luc is the given name of Luc Longley, the Australian former professional basketball player and three-time NBA champion with the Chicago Bulls.
  • B. Lou
    Lou is a supporting character in the romantic drama film "Stuck in Love," involved in the intertwined relationships and personal struggles of a family of writers.
  • C. Lou
    Lou is the central canine hero of the animated film "Cats & Dogs," leading the fight to protect humanity from a secret feline plot.
  • D. Lou
    Lou is a character in the television miniseries "The Continental: From the World of John Wick," set in the action-packed criminal underworld of the John Wick franchise.
  • E. Lou
    Lou is a character from the virtual reality co-op shooter game "After the Fall," set in a post-apocalyptic, frozen Los Angeles overrun by mutated creatures.
  • 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_69d883813098819084f5409539723b59 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e05bf448190947b9da15fd29d0a completed April 18, 2026, 7:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a005820790c819088d953eeea09328d completed May 10, 2026, 10:04 a.m.
NEDg Description generation batch_6a0059126e588190b531c145f3c155b4 completed May 10, 2026, 10:08 a.m.
NED2 Entity disambiguation (via description) batch_6a0059b5a1f8819089caefc121246739 completed May 10, 2026, 10:11 a.m.
Created at: April 10, 2026, 5:13 a.m.