Triple

T2759703
Position Surface form Disambiguated ID Type / Status
Subject Lina Ruz González E61189 entity
Predicate givenName P17 FINISHED
Object Lina E109668 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: Lina | Statement: [Lina Ruz González, givenName, Lina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lina
Context triple: [Lina Ruz González, givenName, Lina]
  • A. Lina chosen
    Lina is a Native American servant in Toni Morrison’s novel *A Mercy*, whose history of displacement and resilience reflects the novel’s themes of slavery, colonialism, and survival in 17th-century America.
  • 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. Marzelline
    Marzelline is a character in Beethoven's opera "Fidelio," portrayed as the jailer Rocco’s daughter who becomes romantically entangled with the disguised heroine.
  • D. Liliana
    Liliana is a feminine given name, often considered a more elaborate or romantic variant of Lily, used in various cultures around the world.
  • E. Marisa
    Marisa is a feminine given name of Latin origin, commonly used in Spanish- and Italian-speaking cultures.
  • 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_69ab4b7a85bc819094a349b84beb1f2c completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdd2121548190b96f174e6f61f9b5 completed March 7, 2026, 8:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69afbbe2d9cc81909b041635ae793bc3 completed March 10, 2026, 6:36 a.m.
Created at: March 6, 2026, 9:57 p.m.