Triple

T3062058
Position Surface form Disambiguated ID Type / Status
Subject Mary Lou Jepsen E62016 entity
Predicate givenName P17 FINISHED
Object Mary Lou E78439 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: [Mary Lou Jepsen, givenName, Mary Lou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mary Lou
Context triple: [Mary Lou Jepsen, givenName, Mary Lou]
  • A. Mary Lou chosen
    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.
  • B. Maria Andrews
    Maria Andrews is an American woman known primarily as the wife of businessman Neil Bush, a member of the prominent Bush political family.
  • C. Mary-Lou
    Mary-Lou is a timid, kind-hearted schoolgirl who appears as one of the students in Enid Blyton’s Malory Towers series.
  • D. Mabel Jones
    Mabel Jones is the daughter of the fictional diarist and protagonist Bridget Jones from Helen Fielding’s popular "Bridget Jones" series.
  • E. Maria Cooley
    Maria Cooley was the wife of American landscape painter Jasper Francis Cropsey, a prominent figure of the Hudson River School.
  • 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_69ad85793e5c8190a358049bc4a98d8c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ad9e9f33d88190bd481cb7f18ceb91 completed March 8, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69b261e211c0819094ef28112bcad250 completed March 12, 2026, 6:49 a.m.
Created at: March 8, 2026, 3:02 p.m.