Triple

T19511003
Position Surface form Disambiguated ID Type / Status
Subject Constancia y otras novelas para vírgenes E488150 entity
Predicate hasPart P35 FINISHED
Object Constancia NE NERFINISHED

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: Constancia | Statement: [Constancia y otras novelas para vírgenes, hasPart, Constancia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Constancia
Context triple: [Constancia y otras novelas para vírgenes, hasPart, Constancia]
  • A. Constancia chosen
    Constancia is a feminine given name, used as a variant of Constance in various languages and cultures.
  • B. Constanza
    Constanza is a mountainous town in the Dominican Republic known for its cool climate, fertile valleys, and agricultural production.
  • C. Clementina
    Clementina is a feminine given name, often considered a variant of Clementine, used in various European and Latin American cultures.
  • D. Genoveva
    Genoveva is the tragic heroine of Robert Schumann’s only opera, a Romantic-era work based on medieval legend.
  • E. Carmelina
    Carmelina is a lesser-known Broadway musical with music by Burton Lane and lyrics by Alan Jay Lerner, loosely based on the film "Buona Sera, Mrs. Campbell."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8da8bec819081f400199491ccc3 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63516572c8190a8719c51fd3f7147 completed April 20, 2026, 2:15 p.m.
Created at: April 10, 2026, 1:40 p.m.