Triple

T15497151
Position Surface form Disambiguated ID Type / Status
Subject Isabella Clara Eugenia E378847 entity
Predicate givenName P17 FINISHED
Object Clara E94446 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: Clara | Statement: [Isabella Clara Eugenia, givenName, Clara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Clara
Context triple: [Isabella Clara Eugenia, givenName, Clara]
  • A. Clara
    Clara is the young heroine of Tchaikovsky’s ballet "The Nutcracker," whose magical Christmas Eve adventure begins when her toy nutcracker comes to life.
  • B. Clara
    Clara is the central female protagonist of Pedro Almodóvar’s 1997 Spanish drama film "Live Flesh," around whom much of the film’s emotional and narrative tension revolves.
  • C. Clara chosen
    Clara is a feminine given name of Latin origin, derived from "clarus" meaning "bright" or "famous."
  • D. Clara
    Clara is a character in the American folk opera "Porgy and Bess," known as a young mother whose lullaby "Summertime" is one of the work’s most famous songs.
  • E. Clara
    Clara is a small Irish town located in County Offaly, known historically for its milling industry and proximity to the River Brosna.
  • 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03fb0aee081909db1c54349ec8492 completed April 16, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3665769c8190be1af51a82a5e75f completed May 9, 2026, 1:28 p.m.
Created at: April 10, 2026, 3:52 a.m.