Triple

T2272668
Position Surface form Disambiguated ID Type / Status
Subject Larisa Latynina E50695 entity
Predicate givenName P17 FINISHED
Object Larisa
Larisa is a feminine given name of Slavic origin, commonly used in Russia and other Eastern European countries.
 E250192 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: Larisa | Statement: [Larisa Latynina, givenName, Larisa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Larisa
Context triple: [Larisa Latynina, givenName, Larisa]
  • A. Larissa
    Larissa is a major city in central Greece known as an important agricultural, commercial, and transportation hub of the Thessaly region.
  • B. Larissa
    Larissa is one of Neptune’s small, irregularly shaped inner moons, discovered in 1981 and composed primarily of dark, icy material.
  • C. Romeyka
    Romeyka is an endangered Greek dialect spoken mainly in northeastern Turkey, notable for preserving many archaic features of Ancient Greek.
  • D. Kashirina
    Kashirina is a Russian surname most notably borne by Varvara Vasilyevna Kashirina.
  • E. Nadezhda
    Nadezhda is a feminine given name of Slavic origin, commonly used in Russian-speaking countries and meaning "hope."
  • 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: Larisa
Triple: [Larisa Latynina, givenName, Larisa]
Generated description
Larisa is a feminine given name of Slavic origin, commonly used in Russia and other Eastern European countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Larisa
Target entity description: Larisa is a feminine given name of Slavic origin, commonly used in Russia and other Eastern European countries.
  • A. Larissa
    Larissa is a major city in central Greece known as an important agricultural, commercial, and transportation hub of the Thessaly region.
  • B. Larissa
    Larissa is one of Neptune’s small, irregularly shaped inner moons, discovered in 1981 and composed primarily of dark, icy material.
  • C. Romeyka
    Romeyka is an endangered Greek dialect spoken mainly in northeastern Turkey, notable for preserving many archaic features of Ancient Greek.
  • D. Kashirina
    Kashirina is a Russian surname most notably borne by Varvara Vasilyevna Kashirina.
  • E. Nadezhda
    Nadezhda is a feminine given name of Slavic origin, commonly used in Russian-speaking countries and meaning "hope."
  • 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_69a88b05910c8190a9a2b1ff230c85f9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc1e872448190a1d6c6071b2a294b completed March 7, 2026, 6:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae71db927c8190a76cfb873039b04b completed March 9, 2026, 7:08 a.m.
NEDg Description generation batch_69ae7486bf808190a732e5eb7744b087 completed March 9, 2026, 7:19 a.m.
NED2 Entity disambiguation (via description) batch_69ae74eb89448190895fab4a493c6d08 completed March 9, 2026, 7:21 a.m.
Created at: March 4, 2026, 7:48 p.m.