Triple

T4687756
Position Surface form Disambiguated ID Type / Status
Subject Little Fires Everywhere E103961 entity
Predicate developer P73 FINISHED
Object Liz Tigelaar E459859 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: Liz Tigelaar | Statement: [Little Fires Everywhere, developer, Liz Tigelaar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Liz Tigelaar
Context triple: [Little Fires Everywhere, developer, Liz Tigelaar]
  • A. Liz Tigelaar chosen
    Liz Tigelaar is an American television writer and producer known for creating and showrunning character-driven dramas such as the series adaptation of "Little Fires Everywhere."
  • B. Wivina Demeester
    Wivina Demeester is a Belgian politician known for her long-standing role in Flemish and national politics, particularly in public finance and infrastructure.
  • C. Virginia Jansen
    Virginia Jansen is known as the spouse of American choral and orchestral conductor Robert Shaw.
  • D. Emily Damstra
    Emily Damstra is a Canadian-born scientific illustrator and coin designer known for her detailed nature-themed artwork for the U.S. Mint and other institutions.
  • E. Francine Houben
    Francine Houben is a renowned Dutch architect and creative director of the architecture firm Mecanoo, known for her human-centered, context-sensitive designs such as the Library of Birmingham and Delft University of Technology Library.
  • 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_69bd43debbf08190b4bc372e286ec234 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd6397f6888190a9024a51d4d34f2b completed March 20, 2026, 3:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69be105a709c819083504fe1dc1612d8 completed March 21, 2026, 3:28 a.m.
Created at: March 20, 2026, 1:16 p.m.