Triple

T15625602
Position Surface form Disambiguated ID Type / Status
Subject Mike and Dave Need Wedding Dates E375667 entity
Predicate mainCharacter P1183 FINISHED
Object Mike Stangle E1213591 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: Mike Stangle | Statement: [Mike and Dave Need Wedding Dates, mainCharacter, Mike Stangle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mike Stangle
Context triple: [Mike and Dave Need Wedding Dates, mainCharacter, Mike Stangle]
  • A. Mike Stangle chosen
    Mike Stangle is a co-author of the humorous memoir "Mike and Dave Need Wedding Dates," which inspired the film of the same name.
  • B. Mike Stroud
    Mike Stroud is an American musician and guitarist best known as one half of the electronic rock duo Ratatat.
  • C. Curtis Stigers
    Curtis Stigers is an American jazz and soul-influenced singer, saxophonist, and songwriter known for his early 1990s pop hits and later critically acclaimed jazz recordings.
  • D. Chris Stolte
    Chris Stolte is a computer scientist and entrepreneur best known as a co-founder and former chief development officer of the data visualization company Tableau Software.
  • E. Mike Stamm
    Mike Stamm is an American backstroke swimmer and Olympic medalist who competed for the United States in the early 1970s.
  • 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_69d85cd035a48190b73d5579ab73969a completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e9e5e248190ae54cda1fde51efb completed April 16, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00580789c08190994c5c71525aadc6 completed May 10, 2026, 10:03 a.m.
Created at: April 10, 2026, 4:14 a.m.