Triple

T11461801
Position Surface form Disambiguated ID Type / Status
Subject Natalya Kirillovna Naryshkina E271677 entity
Predicate givenName P17 FINISHED
Object Natalya E281523 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: Natalya | Statement: [Natalya Kirillovna Naryshkina, givenName, Natalya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Natalya
Context triple: [Natalya Kirillovna Naryshkina, givenName, Natalya]
  • A. Natalya chosen
    Natalya is a feminine given name of Slavic origin, commonly used in Russian-speaking countries and derived from the Latin name Natalia.
  • B. Natalia
    Natalia was a short-lived Boer republic established in the 1830s in what is now KwaZulu-Natal, South Africa.
  • C. Yelena
    Yelena is a feminine given name of Slavic origin, commonly used in Russian-speaking countries and equivalent to Helen or Helena in English.
  • D. Nadya
    Nadya is a feminine given name, often used as a diminutive of Nadezhda in Slavic cultures.
  • E. Наташа
    Наташа — одна из главных героинь пьесы Максима Горького «На дне», олицетворяющая трагическую судьбу бедной и угнетённой женщины в мире социального дна.
  • 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_69d6aae0c8d881908a5a360c0be3242e completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d822f384f08190b1150ed1389dd31a completed April 9, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69e60415f6ac8190ad81ed0ef0a30e12 completed April 20, 2026, 10:46 a.m.
Created at: April 8, 2026, 9:35 p.m.