Triple

T8072006
Position Surface form Disambiguated ID Type / Status
Subject Khokhlova E188395 entity
Predicate hasMasculineForm P15475 FINISHED
Object Khokhlov E709709 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: Khokhlov | Statement: [Khokhlova, hasMasculineForm, Khokhlov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Khokhlov
Context triple: [Khokhlova, hasMasculineForm, Khokhlov]
  • A. Khokhlov chosen
    Khokhlov is a Russian surname commonly found in Eastern Europe, typically indicating Slavic heritage.
  • B. Khovrino
    Khovrino is a Moscow Metro station serving as the northern terminus of the Zamoskvoretskaya Line.
  • C. Yuryatin
    Yuryatin is a fictional Russian town in Boris Pasternak’s novel "Doctor Zhivago," serving as a key setting in Lara Antipova’s story.
  • D. Vyazemsky
    Vyazemsky is a small town in Russia’s Far Eastern Federal District, serving as an administrative center within Khabarovsk Krai.
  • E. Kamenskiy
    Kamenskiy is a Slavic surname, commonly transliterated from Russian or related languages, borne by various individuals across Eastern Europe and the former Soviet Union.
  • 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_69ca82b50c708190863f661d438e68df completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4046a2148190a584e33bcf53cf22 completed March 31, 2026, 3:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc93e568388190a518baa0badefea4 completed April 1, 2026, 3:41 a.m.
Created at: March 30, 2026, 5:27 p.m.