Triple

T3748134
Position Surface form Disambiguated ID Type / Status
Subject Millicent Siegel E81258 entity
Predicate givenName P17 FINISHED
Object Millicent E361596 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: Millicent | Statement: [Millicent Siegel, givenName, Millicent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Millicent
Context triple: [Millicent Siegel, givenName, Millicent]
  • A. Millicent chosen
    Millicent is the given first name of actress Barbara Bain, known for her roles in the television series "Mission: Impossible" and "Space: 1999."
  • B. Marjorie
    Marjorie is a feminine given name of French origin that has been widely used in English-speaking countries.
  • C. Leatrice Joy
    Leatrice Joy was a prominent American silent film actress of the 1920s known for her expressive performances and distinctive bobbed hairstyle.
  • D. Mollie Malloy
    Mollie Malloy is a supporting character in the classic newsroom comedy "The Front Page," often portrayed as a vulnerable woman entangled in the central murder case and exploited by the press.
  • E. Mildred
    Mildred is a feminine given name of English origin that became especially popular in the late 19th and early 20th centuries.
  • 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_69ad8b19b7b08190a6188804e99c53e9 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb6ac5ac8190934ec1a6c887a8f5 completed March 8, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4db2f5e9881908c10feafbb569f48 completed March 14, 2026, 3:51 a.m.
Created at: March 8, 2026, 3:35 p.m.