Triple

T5061048
Position Surface form Disambiguated ID Type / Status
Subject Stepan Arkadyevich Oblonsky E114021 entity
Predicate alsoKnownAs P39 FINISHED
Object Stiva
Stiva is the familiar nickname of Stepan Arkadyevich Oblonsky, a charming, pleasure-loving Moscow nobleman and key supporting character in Leo Tolstoy’s novel "Anna Karenina."
 E490860 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: Stiva | Statement: [Stepan Arkadyevich Oblonsky, alsoKnownAs, Stiva]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Stiva
Context triple: [Stepan Arkadyevich Oblonsky, alsoKnownAs, Stiva]
  • A. Stanca
    Stanca was the wife of Michael the Brave, the late 16th-century prince who briefly united Wallachia, Transylvania, and Moldavia.
  • B. Stiris
    Stiris was an ancient Greek city in the region of Phocis, known as one of its notable urban centers in classical antiquity.
  • C. Stavka
    Stavka was the high command of the Soviet armed forces during World War II, responsible for overall strategic direction and coordination of military operations.
  • D. Stod
    Stod is a small town in the Plzeň Region of the Czech Republic that serves as a local administrative and service center for surrounding municipalities.
  • E. Siatista
    Siatista is a historic town in Western Macedonia, Greece, known for its traditional mansions, fur trade, and cultural heritage.
  • 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: Stiva
Triple: [Stepan Arkadyevich Oblonsky, alsoKnownAs, Stiva]
Generated description
Stiva is the familiar nickname of Stepan Arkadyevich Oblonsky, a charming, pleasure-loving Moscow nobleman and key supporting character in Leo Tolstoy’s novel "Anna Karenina."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Stiva
Target entity description: Stiva is the familiar nickname of Stepan Arkadyevich Oblonsky, a charming, pleasure-loving Moscow nobleman and key supporting character in Leo Tolstoy’s novel "Anna Karenina."
  • A. Stanca
    Stanca was the wife of Michael the Brave, the late 16th-century prince who briefly united Wallachia, Transylvania, and Moldavia.
  • B. Stiris
    Stiris was an ancient Greek city in the region of Phocis, known as one of its notable urban centers in classical antiquity.
  • C. Stavka
    Stavka was the high command of the Soviet armed forces during World War II, responsible for overall strategic direction and coordination of military operations.
  • D. Stod
    Stod is a small town in the Plzeň Region of the Czech Republic that serves as a local administrative and service center for surrounding municipalities.
  • E. Siatista
    Siatista is a historic town in Western Macedonia, Greece, known for its traditional mansions, fur trade, and cultural heritage.
  • 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_69bd443c0c8c81908663b77afb28e165 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd74740ae08190930f1fd57187334e completed March 20, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea49566548190bc6328996789ad9f completed March 21, 2026, 2 p.m.
NEDg Description generation batch_69bea575fa448190b64b6d6305a8d5a6 completed March 21, 2026, 2:04 p.m.
NED2 Entity disambiguation (via description) batch_69bea60244c88190850ac256e290c190 completed March 21, 2026, 2:06 p.m.
Created at: March 20, 2026, 1:38 p.m.