Triple

T199841
Position Surface form Disambiguated ID Type / Status
Subject Gunnar Nelson E4078 entity
Predicate givenName P17 FINISHED
Object Gunnar
Gunnar is a masculine given name of Old Norse origin, commonly used in Scandinavian countries and associated with warriors or bold fighters.
 E30461 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: Gunnar | Statement: [Gunnar Nelson, givenName, Gunnar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gunnar
Context triple: [Gunnar Nelson, givenName, Gunnar]
  • A. Audun Tron
    Audun Tron is a Norwegian politician who served as the mayor of Lillehammer during the period when the city hosted the 1994 Winter Olympics.
  • B. 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.
  • C. Jóhan
    Jóhan is a given name, primarily used in Faroese and other Nordic contexts, that corresponds to the name Johan.
  • D. Johanus
    Johanus is a given name, likely a variant or diminutive of Johan, used as a personal first name in some cultures.
  • E. Gustaf
    Gustaf is the given name of Carl Gustaf Emil Mannerheim, the Finnish military leader and statesman who served as Commander-in-Chief during World War II and later as President of Finland.
  • 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: Gunnar
Triple: [Gunnar Nelson, givenName, Gunnar]
Generated description
Gunnar is a masculine given name of Old Norse origin, commonly used in Scandinavian countries and associated with warriors or bold fighters.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gunnar
Target entity description: Gunnar is a masculine given name of Old Norse origin, commonly used in Scandinavian countries and associated with warriors or bold fighters.
  • A. Audun Tron
    Audun Tron is a Norwegian politician who served as the mayor of Lillehammer during the period when the city hosted the 1994 Winter Olympics.
  • B. 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.
  • C. Jóhan
    Jóhan is a given name, primarily used in Faroese and other Nordic contexts, that corresponds to the name Johan.
  • D. Johanus
    Johanus is a given name, likely a variant or diminutive of Johan, used as a personal first name in some cultures.
  • E. Gustaf
    Gustaf is the given name of Carl Gustaf Emil Mannerheim, the Finnish military leader and statesman who served as Commander-in-Chief during World War II and later as President of Finland.
  • 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_69a254bca59881909a15e1496f1508c7 completed Feb. 28, 2026, 2:36 a.m.
NER Named-entity recognition batch_69a25bcc6dc88190b8c24b485588dfe4 completed Feb. 28, 2026, 3:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3672e822c8190be0d6c0714034ff7 completed Feb. 28, 2026, 10:07 p.m.
NEDg Description generation batch_69a367bc6cb48190b5bc588db0833474 completed Feb. 28, 2026, 10:10 p.m.
NED2 Entity disambiguation (via description) batch_69a3681d99a881908ea8d2632ba2aab1 completed Feb. 28, 2026, 10:11 p.m.
Created at: Feb. 28, 2026, 2:44 a.m.