Triple

T1837489
Position Surface form Disambiguated ID Type / Status
Subject Kyösti Kallio E41097 entity
Predicate givenName P17 FINISHED
Object Kyösti
Kyösti is a Finnish masculine given name, notably borne by Kyösti Kallio, the fourth President of Finland.
E205324 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: Kyösti | Statement: [Kyösti Kallio, givenName, Kyösti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kyösti
Context triple: [Kyösti Kallio, givenName, Kyösti]
  • A. Kooda
    "Kooda" is a high-energy hip-hop single by rapper Tekashi 6ix9ine, known for its aggressive delivery and colorful, chaotic music video that helped launch his mainstream notoriety.
  • B. Sivaraksa
    Sivaraksa is the surname of Sulak Sivaraksa, a prominent Thai social activist, intellectual, and proponent of engaged Buddhism.
  • C. Vitasta
    Vitasta is the ancient Sanskrit name for the Jhelum River, a historically significant river of the Kashmir region frequently mentioned in Vedic and classical Indian texts.
  • D. Parainen
    Parainen is a coastal town and municipality in southwestern Finland known for its archipelago landscape and maritime heritage.
  • E. Mo i Rana
    Mo i Rana is an industrial town in Nordland county, Norway, known for its steel industry, proximity to the Arctic Circle, and role as a regional hub in Northern Norway.
  • 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: Kyösti
Triple: [Kyösti Kallio, givenName, Kyösti]
Generated description
Kyösti is a Finnish masculine given name, notably borne by Kyösti Kallio, the fourth President of Finland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kyösti
Target entity description: Kyösti is a Finnish masculine given name, notably borne by Kyösti Kallio, the fourth President of Finland.
  • A. Kooda
    "Kooda" is a high-energy hip-hop single by rapper Tekashi 6ix9ine, known for its aggressive delivery and colorful, chaotic music video that helped launch his mainstream notoriety.
  • B. Sivaraksa
    Sivaraksa is the surname of Sulak Sivaraksa, a prominent Thai social activist, intellectual, and proponent of engaged Buddhism.
  • C. Vitasta
    Vitasta is the ancient Sanskrit name for the Jhelum River, a historically significant river of the Kashmir region frequently mentioned in Vedic and classical Indian texts.
  • D. Parainen
    Parainen is a coastal town and municipality in southwestern Finland known for its archipelago landscape and maritime heritage.
  • E. Mo i Rana
    Mo i Rana is an industrial town in Nordland county, Norway, known for its steel industry, proximity to the Arctic Circle, and role as a regional hub in Northern Norway.
  • 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_69a88647f9388190909bc36e795bdaec completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb0380a4c81909a2ad0bfd97c884a completed March 7, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69adc9b6dc9481908a83e60aee326bc4 completed March 8, 2026, 7:10 p.m.
NEDg Description generation batch_69adcaef04e88190a88f789a6370bafb completed March 8, 2026, 7:15 p.m.
NED2 Entity disambiguation (via description) batch_69adcb8e053c819082a3d4b36afe35be completed March 8, 2026, 7:18 p.m.
Created at: March 4, 2026, 7:33 p.m.