Triple

T7595362
Position Surface form Disambiguated ID Type / Status
Subject Doom Patrol E179843 entity
Predicate stars P1956 FINISHED
Object Alan Tudyk E197222 NE FINISHED

How this triple was built (2 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: Alan Tudyk | Statement: [Doom Patrol, stars, Alan Tudyk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alan Tudyk
Context triple: [Doom Patrol, stars, Alan Tudyk]
  • A. Alan Tudyk chosen
    Alan Tudyk is an American actor and voice actor known for his versatile character roles in films, television, and animation, including work with Disney and on series like "Firefly."
  • B. Marc Tarpenning
    Marc Tarpenning is an American engineer and entrepreneur best known as a co-founder of electric vehicle and clean energy company Tesla, Inc.
  • C. Fran Kranz
    Fran Kranz is an American actor best known for his roles in the TV series "Dollhouse" and the horror-comedy film "The Cabin in the Woods."
  • D. Sean Gunn
    Sean Gunn is an American actor best known for playing Kraglin in the Marvel Cinematic Universe and for his role as Kirk Gleason on the television series Gilmore Girls.
  • E. Connor Trinneer
    Connor Trinneer is an American actor best known for his role as Commander Charles "Trip" Tucker III on the science fiction television series Star Trek: Enterprise.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c69f3487ec8190bf7acdf2dd91e6d6 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f9bbcd8081909a229d7faa2ffdc8 completed March 27, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8619d6f2081908c8b589d4106691f completed March 28, 2026, 11:17 p.m.
Created at: March 27, 2026, 3:53 p.m.