Triple

T12774462
Position Surface form Disambiguated ID Type / Status
Subject Sea and Sardinia E305330 entity
Predicate relatedWork P37 FINISHED
Object Twilight in Italy E305331 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: Twilight in Italy | Statement: [Sea and Sardinia, relatedWork, Twilight in Italy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Twilight in Italy
Context triple: [Sea and Sardinia, relatedWork, Twilight in Italy]
  • A. Twilight in Italy chosen
    "Twilight in Italy" is a 1916 travel book by D. H. Lawrence that blends vivid descriptions of the Italian landscape with personal reflections and cultural observations.
  • B. A Song of Italy
    A Song of Italy is a politically charged poem by Algernon Charles Swinburne celebrating Italian unification and republican ideals.
  • C. The Italian Woman
    The Italian Woman is a 1915 American silent drama film directed by Reginald Barker and starring Clara Williams.
  • D. The Italian Dragon
    The Italian Dragon is the ring nickname of Joe Calzaghe, the undefeated Welsh former world champion boxer of Italian descent.
  • E. My House in Umbria
    My House in Umbria is a 2003 television drama film, based on William Trevor’s novel, about a British romance novelist in Italy who shelters survivors after a terrorist attack.
  • 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_69d7bdf2b43c819098ae5aa68e61ea58 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96df6b3c88190b0bbe70de8ddcbf3 completed April 10, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69f684fee60c81909245d4d70c9338c0 completed May 2, 2026, 11:13 p.m.
Created at: April 9, 2026, 5:29 p.m.