Triple

T16716694
Position Surface form Disambiguated ID Type / Status
Subject Wendie Malick E406242 entity
Predicate televisionSeries P3279 FINISHED
Object Fillmore! E857145 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: Fillmore! | Statement: [Wendie Malick, televisionSeries, Fillmore!]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fillmore!
Context triple: [Wendie Malick, televisionSeries, Fillmore!]
  • A. Fillmore! chosen
    Fillmore! is an early-2000s animated television series that parodies police procedurals by following a pair of safety patrol officers solving crimes in a middle school setting.
  • B. Fillmore
    Fillmore is a small agricultural city in Ventura County, California, known for its historic downtown and citrus and avocado groves.
  • C. Fillmore
    Fillmore is a small city in central Utah that briefly served as the territorial capital in the mid-19th century and is now a local agricultural and service hub.
  • D. Fillmore
    Fillmore is a surname most notably associated with Millard Fillmore, the 13th president of the United States, and his wife Abigail Fillmore.
  • E. Fillmore
    Fillmore is a laid-back, hippie Volkswagen bus character from Pixar's Cars franchise known for his love of organic fuel and groovy lifestyle.
  • 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_69d8838f242881908abd8bc138795886 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e38656b66081909f2c2a8971c45aee completed April 18, 2026, 1:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0091ab9e54819097e71ce1616b28b5 completed May 10, 2026, 2:09 p.m.
Created at: April 10, 2026, 5:20 a.m.