Triple

T1854386
Position Surface form Disambiguated ID Type / Status
Subject Akseli Gallen-Kallela E41668 entity
Predicate givenName P17 FINISHED
Object Axel
Axel is a given name associated with the Finnish painter Akseli Gallen-Kallela, renowned for his depictions of the Kalevala and contributions to Finnish national romantic art.
 E206489 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: Axel | Statement: [Akseli Gallen-Kallela, givenName, Axel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Axel
Context triple: [Akseli Gallen-Kallela, givenName, Axel]
  • A. 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.
  • B. Lars
    Lars is a masculine given name of Scandinavian origin, commonly used in countries such as Norway, Sweden, and Denmark.
  • C. Johan
    Johan is the given first name of J. Erik Jonsson, an American businessman and philanthropist who co-founded Texas Instruments and served as mayor of Dallas.
  • D. Lukas
    Lukas is a masculine given name commonly used in various European countries, often associated with the biblical name Luke.
  • E. Niels
    Niels is the given name of the pioneering Norwegian mathematician Niels Henrik Abel, known for his foundational work in algebra and analysis.
  • 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: Axel
Triple: [Akseli Gallen-Kallela, givenName, Axel]
Generated description
Axel is a given name associated with the Finnish painter Akseli Gallen-Kallela, renowned for his depictions of the Kalevala and contributions to Finnish national romantic art.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Axel
Target entity description: Axel is a given name associated with the Finnish painter Akseli Gallen-Kallela, renowned for his depictions of the Kalevala and contributions to Finnish national romantic art.
  • A. 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.
  • B. Lars
    Lars is a masculine given name of Scandinavian origin, commonly used in countries such as Norway, Sweden, and Denmark.
  • C. Johan
    Johan is the given first name of J. Erik Jonsson, an American businessman and philanthropist who co-founded Texas Instruments and served as mayor of Dallas.
  • D. Lukas
    Lukas is a masculine given name commonly used in various European countries, often associated with the biblical name Luke.
  • E. Niels
    Niels is the given name of the pioneering Norwegian mathematician Niels Henrik Abel, known for his foundational work in algebra and analysis.
  • 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_69a8864a83848190a4ec02721306c511 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb07d48c48190bcd34d6093ff5e78 completed March 7, 2026, 4:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69adc9c9c6208190a2793994a7f927bd completed March 8, 2026, 7:11 p.m.
NEDg Description generation batch_69adcaf23e748190a031625208f4cf17 completed March 8, 2026, 7:16 p.m.
NED2 Entity disambiguation (via description) batch_69adcbf835b48190aaeb61f34f6aafdc completed March 8, 2026, 7:20 p.m.
Created at: March 4, 2026, 7:33 p.m.