Triple

T5779158
Position Surface form Disambiguated ID Type / Status
Subject Bring Him Home E127514 entity
Predicate lyricSubject P4921 FINISHED
Object safety of Marius Pontmercy E130843 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: safety of Marius Pontmercy | Statement: [Bring Him Home, lyricSubject, safety of Marius Pontmercy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: safety of Marius Pontmercy
Context triple: [Bring Him Home, lyricSubject, safety of Marius Pontmercy]
  • A. Marius Pontmercy chosen
    Marius Pontmercy is a central character in Victor Hugo’s novel *Les Misérables*, a young idealistic law student and revolutionary who falls in love with Cosette.
  • B. Sophia Subercaseaux
    Sophia Subercaseaux is an editor known for her work on the novel "The Devil All the Time."
  • C. Julien
    Julien is a given name of French origin commonly used for males in various Francophone and European countries.
  • D. Jules
    Jules is a given name most famously associated with French poet Jules Laforgue, a key figure in Symbolist and early modernist literature.
  • E. Éponine
    Éponine is a tragic, lovestruck young woman in Victor Hugo’s Les Misérables, known for her unrequited love for Marius and her poignant solo “On My Own” in the 2012 film adaptation.
  • 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_69c008361fa88190aefa4dc41b051e7f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c029e26ff88190b7f8eb03bcd30dc6 completed March 22, 2026, 5:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07e735f408190b188b94131f1e51b completed March 22, 2026, 11:42 p.m.
Created at: March 22, 2026, 3:50 p.m.