Triple

T16026992
Position Surface form Disambiguated ID Type / Status
Subject Afanasy Danilovich E388740 entity
Predicate givenName P17 FINISHED
Object Afanasy
Afanasy is a Russian masculine given name of Greek origin, commonly borne by historical and religious figures in Slavic cultures.
E1189190 NE FINISHED

How this triple was built (4 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: Afanasy | Statement: [Afanasy Danilovich, givenName, Afanasy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Afanasy
Context triple: [Afanasy Danilovich, givenName, Afanasy]
  • A. Vorontsovskaya
    Vorontsovskaya is a metro station on Moscow’s Big Circle Line serving the southwestern part of the city.
  • B. Vyatka
    Vyatka was a historic region and town in northeastern European Russia, known as a frontier area that was gradually incorporated into the centralized Russian state.
  • C. Anatoli
    Anatoli is a small village in Greece that forms part of the Agia municipality in the regional unit of Larissa.
  • D. Khovrino
    Khovrino is a Moscow Metro station serving as the northern terminus of the Zamoskvoretskaya Line.
  • E. Dobryninskaya
    Dobryninskaya is a Moscow Metro station on the circular Koltsevaya Line, known for its Stalinist-era architecture and central location.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Afanasy
Triple: [Afanasy Danilovich, givenName, Afanasy]
Generated description
Afanasy is a Russian masculine given name of Greek origin, commonly borne by historical and religious figures in Slavic cultures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Afanasy
Target entity description: Afanasy is a Russian masculine given name of Greek origin, commonly borne by historical and religious figures in Slavic cultures.
  • A. Vorontsovskaya
    Vorontsovskaya is a metro station on Moscow’s Big Circle Line serving the southwestern part of the city.
  • B. Vyatka
    Vyatka was a historic region and town in northeastern European Russia, known as a frontier area that was gradually incorporated into the centralized Russian state.
  • C. Anatoli
    Anatoli is a small village in Greece that forms part of the Agia municipality in the regional unit of Larissa.
  • D. Khovrino
    Khovrino is a Moscow Metro station serving as the northern terminus of the Zamoskvoretskaya Line.
  • E. Dobryninskaya
    Dobryninskaya is a Moscow Metro station on the circular Koltsevaya Line, known for its Stalinist-era architecture and central location.
  • F. None of above. chosen

Provenance (5 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_69d86dada3808190825d5f80d72fbe88 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e18328707c8190b9a444c78faaaa04 completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf33c6a881909284933ea3b7dd6e completed May 10, 2026, 12:20 a.m.
NEDg Description generation batch_69ffd01d545c8190a96cd888223c7fa9 completed May 10, 2026, 12:23 a.m.
NED2 Entity disambiguation (via description) batch_69ffd0b3d4b08190b1be30954d5d76c0 completed May 10, 2026, 12:26 a.m.
Created at: April 10, 2026, 4:56 a.m.