Triple

T13550113
Position Surface form Disambiguated ID Type / Status
Subject Veronica Rawlings E323618 entity
Predicate filmWriterOfWork P64760 FINISHED
Object Gillian Flynn E323615 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: Gillian Flynn | Statement: [Veronica Rawlings, filmWriterOfWork, Gillian Flynn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gillian Flynn
Context triple: [Veronica Rawlings, filmWriterOfWork, Gillian Flynn]
  • A. Gillian Flynn chosen
    Gillian Flynn is an American author and screenwriter best known for her dark psychological thrillers such as "Gone Girl," many of which have been adapted for film and television.
  • B. Paula Hawkins
    Paula Hawkins is a British author best known for her psychological thriller novel "The Girl on the Train," which was adapted into the 2016 film of the same name.
  • C. Dina Meyer
    Dina Meyer is an American actress best known for her roles in science fiction and horror films and television series, including the Saw franchise and Birds of Prey.
  • D. Alice Sebold
    Alice Sebold is an American author best known for her novels "The Lovely Bones" and "The Almost Moon," as well as her memoir "Lucky."
  • E. Lionel Shriver
    Lionel Shriver is an American author best known for her provocative, psychologically incisive novels such as "We Need to Talk About Kevin."
  • 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_69d8076776248190bdf0d4fa1f85a5fc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafdcecf481909999a173b32a58cd completed April 12, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78add2b0c8190ade1af991744c4e0 completed May 3, 2026, 5:50 p.m.
Created at: April 9, 2026, 9:46 p.m.