Triple

T16073276
Position Surface form Disambiguated ID Type / Status
Subject Oksana E389917 entity
Predicate derivedFrom P909 FINISHED
Object Xenia E158990 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: Xenia | Statement: [Oksana, derivedFrom, Xenia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Xenia
Context triple: [Oksana, derivedFrom, Xenia]
  • A. Xenia chosen
    Xenia is a female given name of Greek origin, commonly used in Slavic and other European cultures.
  • B. Xenia
    Xenia is a collection of epigrammatic poems co-written by Johann Wolfgang von Goethe and Friedrich Schiller that satirically targeted their literary opponents during the Weimar Classicism period.
  • C. Xenia Onatopp
    Xenia Onatopp is a sadistic and lethal assassin from the James Bond film "GoldenEye," notorious for killing her victims with her powerful thighs.
  • D. Xeniya
    Xeniya is a feminine given name, commonly used in Slavic countries as a variant of the name Xenia.
  • E. Alexandera
    Alexandera is a feminine given name, used as a variant form of Alexandra.
  • 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_69d86daf32ec8190a8c0466c8f49c3c0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e183c0390c8190b0da263cccec14e5 completed April 17, 2026, 12:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffe484cef08190a3797c91a7025081 completed May 10, 2026, 1:51 a.m.
Created at: April 10, 2026, 4:57 a.m.