Triple

T23011679
Position Surface form Disambiguated ID Type / Status
Subject San Jose CyberRays E572921 entity
Predicate notablePlayer P304 FINISHED
Object Katya NE NERFINISHED

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: Katya | Statement: [San Jose CyberRays, notablePlayer, Katya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Katya
Context triple: [San Jose CyberRays, notablePlayer, Katya]
  • A. Katya chosen
    Katya is a diminutive and affectionate form of the given name Catherine, commonly used in Slavic and other European cultures.
  • B. Katya Kazanova
    Katya Kazanova is a highly skilled Russian spy and former KGB agent in the animated series "Archer," known for her complex relationship with Sterling Archer and her transformation into a cyborg.
  • C. Lyuba
    Lyuba is a common Slavic diminutive form of the female given name Lyubov, often used as an affectionate nickname.
  • D. Nadya
    Nadya is a feminine given name, often used as a diminutive of Nadezhda in Slavic cultures.
  • E. Nastya
    Nastya is a tragic, idealistic young prostitute in Maxim Gorky’s play "The Lower Depths," known for her romantic fantasies and emotional vulnerability amid harsh social realities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245b764cc8190a51be76f1d9611e1 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1835b0cb881908d3d2dd40cffcbc2 completed April 29, 2026, 4:04 a.m.
Created at: April 17, 2026, 3:51 p.m.