Triple

T8235354
Position Surface form Disambiguated ID Type / Status
Subject Tōshō E192390 entity
Predicate formerMarketSegment P5635 FINISHED
Object Mothers E186737 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: Mothers | Statement: [Tōshō, formerMarketSegment, Mothers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mothers
Context triple: [Tōshō, formerMarketSegment, Mothers]
  • A. Mothers chosen
    Mothers is a section of the Tokyo Stock Exchange dedicated to emerging and high-growth startup companies seeking public investment.
  • B. Mothers Are Women
    Mothers Are Women is a Canadian documentary film by Bonnie Sherr Klein that explores the lives and challenges of disabled mothers.
  • C. Four Mothers
    Four Mothers is a 1941 American drama film that continues the story of the Lemp family introduced in Four Daughters and its first sequel, Four Wives.
  • D. Mother and Child
    "Mother and Child" is a 2009 drama film written and directed by Rodrigo García that interweaves the emotional stories of three women connected by adoption and motherhood.
  • E. Mother and Child
    Mother and Child is a mixed-media painting by Nigerian-born artist Njideka Akunyili Crosby that explores themes of family, identity, and cultural hybridity through layered photographic transfers and figurative imagery.
  • 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_69ca82dc8f148190a2c75a98501a7b91 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb782931848190bcc54622f34e06a7 completed March 31, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd34f0a770819089520e689ca9937a completed April 1, 2026, 3:08 p.m.
Created at: March 30, 2026, 5:46 p.m.