Triple

T17009604
Position Surface form Disambiguated ID Type / Status
Subject Libuše E412662 entity
Predicate character P662 FINISHED
Object Krasava
Krasava is a character from Czech legend and literature associated with the tale of Princess Libuše and the early history of Bohemia.
 E1244601 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: Krasava | Statement: [Libuše, character, Krasava]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Krasava
Context triple: [Libuše, character, Krasava]
  • A. Krasna
    Krasna is a surname most notably associated with American screenwriter, playwright, and film producer Norman Krasna.
  • B. Kras
    Kras is a karst limestone plateau region in southwestern Slovenia and northeastern Italy, renowned for its distinctive caves, sinkholes, and underground rivers that gave the term "karst" to geology.
  • C. Krutov
    Krutov is the namesake of a KLM airline route, likely a notable individual after whom the line was dedicated.
  • D. Kvasy
    Kvasy is a village in western Ukraine’s Zakarpattia region, known as a starting point for hikes in the Carpathian Mountains and for its mineral springs.
  • E. Tsitska
    Tsitska is a Georgian white grape variety from the Imereti region, known for producing fresh, high-acidity wines often used in both still and sparkling styles.
  • 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: Krasava
Triple: [Libuše, character, Krasava]
Generated description
Krasava is a character from Czech legend and literature associated with the tale of Princess Libuše and the early history of Bohemia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Krasava
Target entity description: Krasava is a character from Czech legend and literature associated with the tale of Princess Libuše and the early history of Bohemia.
  • A. Krasna
    Krasna is a surname most notably associated with American screenwriter, playwright, and film producer Norman Krasna.
  • B. Kras
    Kras is a karst limestone plateau region in southwestern Slovenia and northeastern Italy, renowned for its distinctive caves, sinkholes, and underground rivers that gave the term "karst" to geology.
  • C. Krutov
    Krutov is the namesake of a KLM airline route, likely a notable individual after whom the line was dedicated.
  • D. Kvasy
    Kvasy is a village in western Ukraine’s Zakarpattia region, known as a starting point for hikes in the Carpathian Mountains and for its mineral springs.
  • E. Tsitska
    Tsitska is a Georgian white grape variety from the Imereti region, known for producing fresh, high-acidity wines often used in both still and sparkling styles.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d47a8444819081f1262eb7dbda40 completed April 18, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dc241ec88190a3e868ab88b26f09 completed May 10, 2026, 7:27 p.m.
NEDg Description generation batch_6a0114d7d03c8190943777f4eac956fd completed May 10, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a01159a08b081908fc82adc7cca532a completed May 10, 2026, 11:32 p.m.
Created at: April 10, 2026, 5:33 a.m.