Triple

T23274239
Position Surface form Disambiguated ID Type / Status
Subject Skid E588371 entity
Predicate hasPart P35 FINISHED
Object An Awful Lot of Woman 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: An Awful Lot of Woman | Statement: [Skid, hasPart, An Awful Lot of Woman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: An Awful Lot of Woman
Context triple: [Skid, hasPart, An Awful Lot of Woman]
  • A. “An Awful Lot of Woman” chosen
    “An Awful Lot of Woman” is a song by the Irish rock band Skid Row, known for their early 1970s hard rock and blues-influenced sound.
  • B. Such a Woman
    "Such a Woman" is a song by Neil Young featured on his 1992 album "Harvest Moon."
  • C. Up the Women
    Up the Women is a British sitcom set in 1910 that follows a group of women in a small English town as they become involved in the suffragette movement.
  • D. Down Among the Women
    Down Among the Women is a feminist novel by Fay Weldon that explores the lives, struggles, and relationships of several generations of women in mid-20th-century Britain.
  • E. Four Women
    "Four Women" is a powerful 1966 song by Nina Simone that portrays the struggles and identities of four Black women, highlighting themes of racism, sexism, and resilience.
  • 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_69e25d148adc819088efbf42672604e9 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f195768b1c8190ae7cbf8c316ae4dd completed April 29, 2026, 5:21 a.m.
Created at: April 17, 2026, 4:47 p.m.