Triple

T10693965
Position Surface form Disambiguated ID Type / Status
Subject Tanaquil Le Clercq E252081 entity
Predicate hasGivenName P17 FINISHED
Object Tanaquil E246021 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: Tanaquil | Statement: [Tanaquil Le Clercq, hasGivenName, Tanaquil]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tanaquil
Context triple: [Tanaquil Le Clercq, hasGivenName, Tanaquil]
  • A. Tanaquil chosen
    Tanaquil was a celebrated American ballerina and principal dancer with the New York City Ballet, renowned for her collaborations with George Balanchine in the mid-20th century.
  • B. Leontia
    Leontia was a Byzantine imperial princess, the daughter of Emperor Leo I, known for her role in dynastic marriage alliances of the Eastern Roman Empire.
  • C. Tanaquil (traditional attribution)
    Tanaquil is a semi-legendary Etruscan noblewoman in early Roman tradition, renowned for her political influence and prophetic abilities in shaping Rome’s monarchy.
  • D. Leontine
    Leontine is a feminine given name, used as a variant of names like Leona and Leontina, with roots in Latin meaning "lion-like" or "lioness."
  • E. Serafima
    Serafima is a feminine given name of Slavic origin, commonly used in Russian-speaking countries.
  • 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_69d6aa5bd7c08190a816e733b4045c23 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fd38c24c8190a105a9dfdf705b38 completed April 9, 2026, 1:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69d988b002f88190921af43e551ccb85 completed April 10, 2026, 11:33 p.m.
Created at: April 8, 2026, 9:11 p.m.