Triple

T20015101
Position Surface form Disambiguated ID Type / Status
Subject Romanza E494695 entity
Predicate containsSong P20452 FINISHED
Object Miserere 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: Miserere | Statement: [Romanza, containsSong, Miserere]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miserere
Context triple: [Romanza, containsSong, Miserere]
  • A. Miserere
    Miserere is a sacred choral composition by Jean-Baptiste Lully, reflecting the grand liturgical style of the French Baroque.
  • B. Miserere
    Miserere is a contemplative choral and orchestral composition by Arvo Pärt that exemplifies his minimalist, spiritually focused tintinnabuli style.
  • C. Miserere chosen
    Miserere is the traditional Latin title of Psalm 51, a penitential psalm from the Bible widely used in Christian liturgy and musical settings.
  • D. Manciano La Misericordia
    Manciano La Misericordia is a small locality in Italy best known as the birthplace of actor and filmmaker Roberto Benigni.
  • E. Lachrymae Christi
    "Lachrymae Christi" is a poem by Hart Crane, included in his influential 1926 collection *White Buildings*, that reflects his dense, modernist style and visionary imagery.
  • 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_69da626bfd288190aa5d65098b6433ae completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6623bba1881908440c92f08729ec1 completed April 20, 2026, 5:28 p.m.
Created at: April 11, 2026, 3:34 p.m.