Triple

T14630885
Position Surface form Disambiguated ID Type / Status
Subject Grosse Pointe Blank E343474 entity
Predicate producer P490 FINISHED
Object Lloyd Segan E1076274 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: Lloyd Segan | Statement: [Grosse Pointe Blank, producer, Lloyd Segan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lloyd Segan
Context triple: [Grosse Pointe Blank, producer, Lloyd Segan]
  • A. Lloyd Segan chosen
    Lloyd Segan is an American television and film producer known for his work on genre and suspense projects, including the 2001 horror film "Bones."
  • B. Glenn Berger
    Glenn Berger is an American screenwriter best known for co-writing major animated films such as the Kung Fu Panda series.
  • C. Gary Tinterow
    Gary Tinterow is an American art historian and museum curator best known for leading the Museum of Fine Arts, Houston and for his scholarship on 19th-century European art.
  • D. Vern Schillinger
    Vern Schillinger is a fictional white supremacist prison leader and one of the primary antagonists on the HBO series "Oz," portrayed by actor J.K. Simmons.
  • E. Michael Vavitch
    Michael Vavitch was a silent-era film actor known for his role in the 1924 drama "The Red Lily."
  • 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_69d822dffc3c8190aa173b90761bffda completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb4a912248190a3df7f821395c776 completed April 14, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff82dfbc28819090cf56f16b5e7c39 completed May 9, 2026, 6:54 p.m.
Created at: April 10, 2026, 1:26 a.m.