Triple

T20819860
Position Surface form Disambiguated ID Type / Status
Subject Dominion E512543 entity
Predicate mainCharacter P1183 FINISHED
Object Michael
Michael is the central protagonist of the card game Dominion’s narrative setting, around whom the game’s implied story of kingdom-building and power struggles revolves.
 E1453013 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: Michael | Statement: [Dominion, mainCharacter, Michael]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Michael
Context triple: [Dominion, mainCharacter, Michael]
  • A. Michael
    Michael is a common masculine given name of Hebrew origin meaning "Who is like God?"
  • B. Michael
    Michael is a central fictional character in the Australian television drama series "The Newsreader," which explores the personal and professional lives of journalists in the 1980s.
  • C. Michael
    Michael is a central figure in the crime drama "Sleepers," whose traumatic experiences and quest for justice drive much of the film’s emotional and moral conflict.
  • D. Michael
    Michael is the conflicted protagonist of the 2006 romantic dramedy "The Last Kiss," whose struggle with commitment and impending fatherhood drives the film’s central emotional tension.
  • E. Michael
    "Michael" is a 1996 fantasy-comedy film starring John Travolta as an unconventional archangel visiting Earth.
  • 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: Michael
Triple: [Dominion, mainCharacter, Michael]
Generated description
Michael is the central protagonist of the card game Dominion’s narrative setting, around whom the game’s implied story of kingdom-building and power struggles revolves.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Michael
Target entity description: Michael is the central protagonist of the card game Dominion’s narrative setting, around whom the game’s implied story of kingdom-building and power struggles revolves.
  • A. Michael
    Michael is a central figure in the crime drama "Sleepers," whose traumatic experiences and quest for justice drive much of the film’s emotional and moral conflict.
  • B. Michael
    Michael is the conflicted protagonist of the 2006 romantic dramedy "The Last Kiss," whose struggle with commitment and impending fatherhood drives the film’s central emotional tension.
  • C. Michael
    "Michael" is a 1996 fantasy-comedy film starring John Travolta as an unconventional archangel visiting Earth.
  • D. Michael
    Michael is a common masculine given name of Hebrew origin meaning "Who is like God?"
  • E. Michael
    Michael is a central fictional character in the Australian television drama series "The Newsreader," which explores the personal and professional lives of journalists in the 1980s.
  • 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_69e0b4ce39108190a6e8e5df4f1c8dc5 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c2f6a65481909a0df78616e185e4 completed April 21, 2026, 12:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a09006d67408190887aef3d7e87904b completed May 16, 2026, 11:40 p.m.
NEDg Description generation batch_6a09017ffbc88190b9fe259ae773ea4f completed May 16, 2026, 11:45 p.m.
NED2 Entity disambiguation (via description) batch_6a0901ed76bc8190815c656c38f13626 completed May 16, 2026, 11:46 p.m.
Created at: April 16, 2026, 12:41 p.m.