Triple

T11339698
Position Surface form Disambiguated ID Type / Status
Subject Margo Gru E268561 entity
Predicate givenName P17 FINISHED
Object Margo E115848 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: Margo | Statement: [Margo Gru, givenName, Margo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margo
Context triple: [Margo Gru, givenName, Margo]
  • A. Margo chosen
    Margo is the responsible and intelligent eldest of Gru’s three adopted daughters in the Despicable Me franchise.
  • B. Margo
    Margo is a feminine given name commonly used in English-speaking countries, often considered a variant of Margot or Margaret.
  • C. Margo
    Margo was a Mexican-American actress and dancer known for her work in Hollywood films of the 1930s and 1940s and for her later stage and television appearances.
  • D. Marnie
    Marnie is a 1964 psychological thriller film directed by Alfred Hitchcock, starring Tippi Hedren and Sean Connery, about a troubled woman with a mysterious past and compulsive thieving.
  • E. Margo Madison
    Margo Madison is a central character in the alternate-history science fiction TV series "For All Mankind," portrayed as a brilliant NASA engineer and later administrator navigating the political and personal challenges of an expanded space race.
  • 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_69d6aacb1f0881908c84a349fd1be047 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea01c6c08190910a6ce8fb7e186d completed April 9, 2026, 6:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69e55645d8bc8190b338c05ee382d5fc completed April 19, 2026, 10:25 p.m.
Created at: April 8, 2026, 9:33 p.m.