Triple

T20610037
Position Surface form Disambiguated ID Type / Status
Subject Silk E506423 entity
Predicate mainCharacter P1183 FINISHED
Object Martha Costello NE NERFINISHED

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: Martha Costello | Statement: [Silk, mainCharacter, Martha Costello]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Martha Costello
Context triple: [Silk, mainCharacter, Martha Costello]
  • A. Martha Costello chosen
    Martha Costello is the ambitious, idealistic barrister protagonist of the British legal drama series "Silk."
  • B. Martha Kearney
    Martha Kearney is a British journalist and broadcaster best known as a prominent presenter on BBC radio and television, including flagship programmes such as Woman’s Hour and The World at One.
  • C. Martha Quinn
    Martha Quinn is an American television personality and one of MTV’s original video jockeys, known for helping define the channel’s early 1980s music culture.
  • D. Martha Hennessy
    Martha Hennessy is an American Catholic peace activist and granddaughter of Dorothy Day, known for her involvement in the Catholic Worker Movement and anti-nuclear protests.
  • E. Martha Farnsworth
    Martha Farnsworth is the strict yet protective headmistress of a Southern girls’ school in the American Civil War–era drama film "The Beguiled" (2017).
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4bb2b4081908fa4a72444120f35 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6aad6f53481908fb242947dda7028 completed April 20, 2026, 10:38 p.m.
Created at: April 16, 2026, 11:41 a.m.