Triple

T12173801
Position Surface form Disambiguated ID Type / Status
Subject Bianca Andreescu E290038 entity
Predicate fullName P16 FINISHED
Object Bianca Vanessa Andreescu E290038 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: Bianca Vanessa Andreescu | Statement: [Bianca Andreescu, fullName, Bianca Vanessa Andreescu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bianca Vanessa Andreescu
Context triple: [Bianca Andreescu, fullName, Bianca Vanessa Andreescu]
  • A. Bianca Andreescu chosen
    Bianca Andreescu is a Canadian professional tennis player best known for winning the 2019 US Open and becoming the first Canadian to claim a Grand Slam singles title.
  • B. Naomi Osaka
    Naomi Osaka is a Japanese professional tennis player and multiple Grand Slam champion known for her powerful baseline game and influential advocacy on social issues.
  • C. Sasha Schreiber
    Sasha Schreiber is the son of actors Naomi Watts and Liev Schreiber.
  • D. Serhiy Ostapenko
    Serhiy Ostapenko was a Ukrainian politician who briefly served as head of government of the Ukrainian People's Republic during its struggle for independence after World War I.
  • E. Alexa Kenin
    Alexa Kenin was an American film and television actress known for her supporting roles in 1980s movies such as "Pretty in Pink" and "Little Darlings."
  • 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_69d6ab4d6c00819095a9a7c35de83cfb completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915dab42881908e2580c631d4d1cf completed April 10, 2026, 3:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f6a9482481909500c216f23fceb4 completed May 2, 2026, 1:05 p.m.
Created at: April 8, 2026, 9:50 p.m.