Triple

T7138411
Position Surface form Disambiguated ID Type / Status
Subject Miss Grayling E166372 entity
Predicate associatedWith P37 FINISHED
Object Mary-Lou E166370 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: Mary-Lou | Statement: [Miss Grayling, associatedWith, Mary-Lou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mary-Lou
Context triple: [Miss Grayling, associatedWith, Mary-Lou]
  • A. Mary-Lou chosen
    Mary-Lou is a timid, kind-hearted schoolgirl who appears as one of the students in Enid Blyton’s Malory Towers series.
  • B. Mary Lou
    Mary Lou is a technology innovator and entrepreneur best known for her pioneering work in display and imaging technologies, including co-founding One Laptop per Child and founding Openwater.
  • C. Marylou
    Marylou is a free-spirited, impulsive young woman who embodies the restless, hedonistic energy of the Beat Generation in Jack Kerouac’s novel "On the Road."
  • D. Mary Ruth
    Mary Ruth is a fictional character featured in the American television sitcom "The Debbie Reynolds Show."
  • E. Mary Jo
    Mary Jo is the given name of Mary Jo Kopechne, the young political campaign specialist who died in the 1969 Chappaquiddick incident involving Senator Ted Kennedy.
  • 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_69c68884a9388190af42f90d1c1a7151 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e694cc3c81908b0d54c2496a0722 completed March 27, 2026, 8:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7a34b99048190a8e77cd0fe253611 completed March 28, 2026, 9:45 a.m.
Created at: March 27, 2026, 2:45 p.m.