Triple

T17990835
Position Surface form Disambiguated ID Type / Status
Subject Flickering Lights E430364 entity
Predicate mainCharacter P1183 FINISHED
Object Peter
Peter is the central protagonist of the Danish dark comedy film "Flickering Lights," around whom the story’s criminal caper and character-driven humor revolve.
E1299871 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: Peter | Statement: [Flickering Lights, mainCharacter, Peter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter
Context triple: [Flickering Lights, mainCharacter, Peter]
  • A. Peter
    Peter is a common male given name of Greek origin, widely used in many languages and cultures, often associated with the meaning "rock" or "stone."
  • B. Peter
    Peter is a central character in Margaret Atwood's novel "The Edible Woman," serving as the protagonist Marian's conventional, marriage-minded fiancé who embodies societal expectations.
  • C. Peter
    Peter is a leading apostle of Jesus in the New Testament, known for his prominent role in the early Christian church and for preaching key messages about Jesus’ resurrection.
  • D. Peter
    Peter is the sensible, rule-abiding leader of Enid Blyton’s Secret Seven children’s detective club.
  • E. Peter
    Peter is a recurring child character in Enid Blyton’s “Wishing-Chair” fantasy series, known for his magical adventures involving a flying chair.
  • 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: Peter
Triple: [Flickering Lights, mainCharacter, Peter]
Generated description
Peter is the central protagonist of the Danish dark comedy film "Flickering Lights," around whom the story’s criminal caper and character-driven humor revolve.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Peter
Target entity description: Peter is the central protagonist of the Danish dark comedy film "Flickering Lights," around whom the story’s criminal caper and character-driven humor revolve.
  • A. Peter
    Peter is a central character in the darkly comedic short film "The New Tenants," around whom much of the film’s tension and absurdity unfolds.
  • B. Peter
    Peter is the central protagonist in the British black comedy film "Death at a Funeral," around whom the chaotic and farcical events of the story unfold.
  • C. Peter
    Peter is a recurring comedic character from the British sketch show "A Bit of Fry & Laurie."
  • D. Peter
    Peter is a character known as a friend and companion of Chinky the pixie in children's fantasy stories.
  • E. Peter
    Peter is the brave young protagonist of Sergei Prokofiev’s symphonic fairy tale "Peter and the Wolf," known for capturing a wolf with the help of his animal friends.
  • 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_69d8b90364248190a37381adea932f42 completed April 10, 2026, 8:46 a.m.
NER Named-entity recognition batch_69e4b29f127c81908b0c4cb3787e002c completed April 19, 2026, 10:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0337acabd481909deced9a61d84ed3 completed May 12, 2026, 2:22 p.m.
NEDg Description generation batch_6a0338cd02808190b650f59fc16bab0d completed May 12, 2026, 2:27 p.m.
NED2 Entity disambiguation (via description) batch_6a033cb498248190a3805cd356832cd0 completed May 12, 2026, 2:44 p.m.
Created at: April 10, 2026, 10:23 a.m.