Triple

T1790523
Position Surface form Disambiguated ID Type / Status
Subject The Martian E39484 entity
Predicate castMember P1668 FINISHED
Object Kristen Wiig E67174 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: Kristen Wiig | Statement: [The Martian, castMember, Kristen Wiig]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kristen Wiig
Context triple: [The Martian, castMember, Kristen Wiig]
  • A. Kristen Wiig chosen
    Kristen Wiig is an American comedian, actress, and writer best known for her work on Saturday Night Live and films such as Bridesmaids.
  • B. Amy Poehler
    Amy Poehler is an American comedian, actress, writer, and producer best known for her work on "Saturday Night Live" and for starring as Leslie Knope on the sitcom "Parks and Recreation."
  • C. Tina Fey
    Tina Fey is an American comedian, writer, actress, and producer best known for her work on "Saturday Night Live" and creating the acclaimed sitcom "30 Rock."
  • D. Anna Kendrick
    Anna Kendrick is an American actress and singer known for her versatile performances in films such as "Pitch Perfect," "Up in the Air," and the musical fantasy "Into the Woods."
  • E. Anna Faris
    Anna Faris is an American actress and comedian best known for her lead role in the Scary Movie film series and her work in both film and television comedy.
  • 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_69a88631854081909723959921e45c2b completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa6512804c8190a5743c10bd37f83f completed March 6, 2026, 5:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69adb5d063d48190aef6796ee3957994 completed March 8, 2026, 5:45 p.m.
Created at: March 4, 2026, 7:32 p.m.