Triple

T10234446
Position Surface form Disambiguated ID Type / Status
Subject Hannes Kolehmainen E243425 entity
Predicate givenName P17 FINISHED
Object Hannes
Hannes is a masculine given name, particularly common in Finland and other Northern European countries.
 E75878 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: Hannes | Statement: [Hannes Kolehmainen, givenName, Hannes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hannes
Context triple: [Hannes Kolehmainen, givenName, Hannes]
  • A. Hans
    Hans is a masculine given name of Germanic origin commonly used in Germanic and Scandinavian countries.
  • B. Sven
    Sven is the lovable reindeer companion in Disney's animated film "Frozen," known for his close bond with Kristoff and his expressive, dog-like personality.
  • C. Jörg
    Jörg is a masculine given name of German origin, commonly used in German-speaking countries.
  • D. Hansi
    Hansi is a historic town in the Hisar district of Haryana, India, known for its ancient forts and archaeological significance.
  • E. Mathias
    Mathias is a surname most notably associated with Bob Mathias, the American decathlete and two-time Olympic gold medalist.
  • 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: Hannes
Triple: [Hannes Kolehmainen, givenName, Hannes]
Generated description
Hannes is a masculine given name, particularly common in Finland and other Northern European countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hannes
Target entity description: Hannes is a masculine given name, particularly common in Finland and other Northern European countries.
  • A. Hans chosen
    Hans is a masculine given name of Germanic origin commonly used in Germanic and Scandinavian countries.
  • B. Sven
    Sven is the lovable reindeer companion in Disney's animated film "Frozen," known for his close bond with Kristoff and his expressive, dog-like personality.
  • C. Jörg
    Jörg is a masculine given name of German origin, commonly used in German-speaking countries.
  • D. Hansi
    Hansi is a historic town in the Hisar district of Haryana, India, known for its ancient forts and archaeological significance.
  • E. Mathias
    Mathias is a surname most notably associated with Bob Mathias, the American decathlete and two-time Olympic gold medalist.
  • F. None of above.

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_69d381b0f97c819085c9b45799a5fb7c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d20cd8708190ba42752597d62008 completed April 7, 2026, 9:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f74c66048190a0ba1cba593cccb5 completed April 9, 2026, 12:48 a.m.
NEDg Description generation batch_69d6fa2ea97081908395048218c0592b completed April 9, 2026, 1 a.m.
NED2 Entity disambiguation (via description) batch_69d6fcb5dc4c8190944a423a9d16a4b8 completed April 9, 2026, 1:11 a.m.
Created at: April 6, 2026, 11:21 a.m.