Triple

T8509043
Position Surface form Disambiguated ID Type / Status
Subject Marcel E201405 entity
Predicate hasFeminineForm P1613 FINISHED
Object Marcella E733554 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: Marcella | Statement: [Marcel, hasFeminineForm, Marcella]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marcella
Context triple: [Marcel, hasFeminineForm, Marcella]
  • A. Marcella chosen
    Marcella is a British crime drama television series centered on a troubled former detective who returns to investigate a string of murders that echo an old case.
  • B. Marcella Spruce
    Marcella Spruce is the sister of American author Tabitha King and a member of the extended King literary family.
  • C. Marica
    Marica is a figure in Roman mythology, often associated with the Latin king Latinus as his mother and sometimes linked to a local water or nymph deity.
  • D. Maeve
    Maeve is a feminine given name of Irish origin, traditionally associated with a legendary queen of Connacht in Irish mythology.
  • E. 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.
  • 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_69ca8320e5748190ac2c585a0bba8193 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe5df74e8819086b1445cc907e371 completed March 31, 2026, 3:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4e3faa0c81908533e9097ed29b26 completed April 2, 2026, 11:08 a.m.
Created at: March 30, 2026, 6:15 p.m.