Triple

T9769992
Position Surface form Disambiguated ID Type / Status
Subject Lillita Louise MacMurray E237097 entity
Predicate hasGivenName P17 FINISHED
Object Lillita E243736 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: Lillita | Statement: [Lillita Louise MacMurray, hasGivenName, Lillita]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lillita
Context triple: [Lillita Louise MacMurray, hasGivenName, Lillita]
  • A. Lillita chosen
    Lillita is the birth name of Lita Grey, the American actress best known for her early silent film work and marriage to Charlie Chaplin.
  • B. Lilia
    Lilia is a feminine given name, often considered a variant of Lily and associated with the elegance and symbolism of the lily flower.
  • C. Lucilla
    Lucilla was a Roman imperial princess and daughter of Emperor Marcus Aurelius who became Empress as the wife of Lucius Verus and was later implicated in a plot against her brother Commodus.
  • D. Rosalinda
    Rosalinda is a feminine given name of Spanish and Italian origin, often interpreted to mean "beautiful rose."
  • E. Liliane
    Liliane is a feminine given name of French origin, notably borne by French heiress and businesswoman Liliane Bettencourt.
  • 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_69ca84d831b8819090322686b47887ce completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda0f1dea08190b89bcc192b068c66 completed April 1, 2026, 10:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1c4154af081908ca743b43ade83c7 completed April 5, 2026, 2:08 a.m.
Created at: March 30, 2026, 8:26 p.m.