Triple

T7561222
Position Surface form Disambiguated ID Type / Status
Subject Darkman E178797 entity
Predicate mainCharacter P1183 FINISHED
Object Peyton Westlake
Peyton Westlake is a disfigured scientist-turned-vigilante who uses synthetic skin and brutal methods to seek revenge in the Darkman film series.
E673188 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: Peyton Westlake | Statement: [Darkman, mainCharacter, Peyton Westlake]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peyton Westlake
Context triple: [Darkman, mainCharacter, Peyton Westlake]
  • A. Addison Clark
    Addison Clark was an American educator and co-founder of Texas Christian University, playing a key role in its early development and leadership.
  • B. Lacey Pemberton
    Lacey Pemberton is a popular high school girl and one of the central characters in John Green’s novel and film adaptation "Paper Towns."
  • C. Madison Pettis
    Madison Pettis is an American actress and model best known for her breakout childhood role in the Disney film "The Game Plan" and subsequent work in television and voice acting.
  • D. Carley Knox
    Carley Knox is a sports executive best known for her leadership role in the WNBA’s Minnesota Lynx organization.
  • E. Addison Richards
    Addison Richards was an American character actor known for his prolific work in film and early television during the 1930s–1950s.
  • 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: Peyton Westlake
Triple: [Darkman, mainCharacter, Peyton Westlake]
Generated description
Peyton Westlake is a disfigured scientist-turned-vigilante who uses synthetic skin and brutal methods to seek revenge in the Darkman film series.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Peyton Westlake
Target entity description: Peyton Westlake is a disfigured scientist-turned-vigilante who uses synthetic skin and brutal methods to seek revenge in the Darkman film series.
  • A. Addison Clark
    Addison Clark was an American educator and co-founder of Texas Christian University, playing a key role in its early development and leadership.
  • B. Lacey Pemberton
    Lacey Pemberton is a popular high school girl and one of the central characters in John Green’s novel and film adaptation "Paper Towns."
  • C. Madison Pettis
    Madison Pettis is an American actress and model best known for her breakout childhood role in the Disney film "The Game Plan" and subsequent work in television and voice acting.
  • D. Carley Knox
    Carley Knox is a sports executive best known for her leadership role in the WNBA’s Minnesota Lynx organization.
  • E. Addison Richards
    Addison Richards was an American character actor known for his prolific work in film and early television during the 1930s–1950s.
  • 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_69c69f2f80288190b95cceb4da92ab2b completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f8f847c48190a1081aa9de7ff945 completed March 27, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c856d0cbfc8190b2cb2b601a7b078c completed March 28, 2026, 10:31 p.m.
NEDg Description generation batch_69c857e2b6b08190ad5236352d0142be completed March 28, 2026, 10:36 p.m.
NED2 Entity disambiguation (via description) batch_69c8587de3588190a209069dfee31a21 completed March 28, 2026, 10:38 p.m.
Created at: March 27, 2026, 3:50 p.m.