Triple

T19934167
Position Surface form Disambiguated ID Type / Status
Subject Sergei Alexeyich Karenin E479130 entity
Predicate familyName P18 FINISHED
Object Karenin
Karenin is a fictional Russian aristocrat best known as the cold, bureaucratic husband of Anna in Leo Tolstoy’s novel "Anna Karenina."
 E1402420 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: Karenin | Statement: [Sergei Alexeyich Karenin, familyName, Karenin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Karenin
Context triple: [Sergei Alexeyich Karenin, familyName, Karenin]
  • A. Kisaan
    Kisaan is an alternative name for the Kisan language, an indigenous Munda language spoken primarily by the Kisan people in parts of eastern India.
  • B. Kiedis
    Kiedis is the surname of Anthony Kiedis, the American singer and frontman of the rock band Red Hot Chili Peppers.
  • C. Kioni
    Kioni is a picturesque seaside village on the Greek island of Ithaca, known for its traditional architecture and scenic harbor.
  • D. Kanije
    Kanije is a historic fortress town in present-day southwestern Hungary that was a key strategic stronghold during the Ottoman–Habsburg conflicts.
  • E. Anka
    Anka is a common diminutive form of the female given name Anna, used in several Slavic and Central European languages.
  • 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: Karenin
Triple: [Sergei Alexeyich Karenin, familyName, Karenin]
Generated description
Karenin is a fictional Russian aristocrat best known as the cold, bureaucratic husband of Anna in Leo Tolstoy’s novel "Anna Karenina."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Karenin
Target entity description: Karenin is a fictional Russian aristocrat best known as the cold, bureaucratic husband of Anna in Leo Tolstoy’s novel "Anna Karenina."
  • A. Kisaan
    Kisaan is an alternative name for the Kisan language, an indigenous Munda language spoken primarily by the Kisan people in parts of eastern India.
  • B. Kiedis
    Kiedis is the surname of Anthony Kiedis, the American singer and frontman of the rock band Red Hot Chili Peppers.
  • C. Kioni
    Kioni is a picturesque seaside village on the Greek island of Ithaca, known for its traditional architecture and scenic harbor.
  • D. Kanije
    Kanije is a historic fortress town in present-day southwestern Hungary that was a key strategic stronghold during the Ottoman–Habsburg conflicts.
  • E. Anka
    Anka is a common diminutive form of the female given name Anna, used in several Slavic and Central European languages.
  • 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_69d8e521855c8190b41871700afc8d6a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65a1553348190a6c4004d3f9a57c5 completed April 20, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a07f6e830c88190be3af821423d89ee completed May 16, 2026, 4:47 a.m.
NEDg Description generation batch_6a07f7ff6c4481909780fb2ff2c3f1ca completed May 16, 2026, 4:52 a.m.
NED2 Entity disambiguation (via description) batch_6a07f8b11d6c8190ad4c7c7711ff2872 completed May 16, 2026, 4:55 a.m.
Created at: April 10, 2026, 1:53 p.m.