Triple

T7949260
Position Surface form Disambiguated ID Type / Status
Subject Francesco Hayez E184572 entity
Predicate notableWork P4 FINISHED
Object Ruth E616149 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: Ruth | Statement: [Francesco Hayez, notableWork, Ruth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ruth
Context triple: [Francesco Hayez, notableWork, Ruth]
  • A. Ruth
    Ruth is a supporting character in the comedy Western film "A Million Ways to Die in the West," known for being a devout Christian prostitute engaged to the protagonist's best friend.
  • B. Ruth
    Ruth is a character in Gilbert and Sullivan's comic opera "The Pirates of Penzance," known as the pirate apprentice Frederic's former nursemaid and a source of much of the opera's humor and confusion.
  • C. Ruth chosen
    "Ruth" is a philosophical novel by Lou Andreas-Salomé that explores themes of identity, love, and spiritual longing through the inner life of its female protagonist.
  • D. Ruth
    Ruth is a feminine given name of Hebrew origin meaning "friend" or "companion," widely used in English-speaking countries.
  • E. Ruth
    Ruth is the given name of Ruth Bader Ginsburg, the pioneering U.S. Supreme Court Justice and prominent advocate for gender equality and civil rights.
  • 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_69ca8291c2008190b1b8832c87814bcf completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3b2d09a4819097aa49e29a5426ec completed March 31, 2026, 3:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe03c7d308190aec1172415be995c completed March 31, 2026, 2:54 p.m.
Created at: March 30, 2026, 5:10 p.m.