Triple

T6605288
Position Surface form Disambiguated ID Type / Status
Subject Maren Svarstad E149101 entity
Predicate givenName P17 FINISHED
Object Maren
Maren is a feminine given name of Scandinavian origin, commonly used in Norway and Denmark.
E601792 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: Maren | Statement: [Maren Svarstad, givenName, Maren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maren
Context triple: [Maren Svarstad, givenName, Maren]
  • A. Sheilia
    Sheilia is a feminine given name, typically considered an alternative spelling of the name Sheila.
  • B. Krista
    Krista is a feminine given name, typically considered a variant of Christina and used in various European and English-speaking countries.
  • C. Karin
    Karin is a feminine given name used in various cultures, often considered a variant of names like Karen or Katherine.
  • D. Bauline
    Bauline is a small coastal town in Newfoundland and Labrador, Canada, located on the Avalon Peninsula near St. John’s.
  • E. Nena
    Nena is a German pop singer and actress best known internationally for her 1983 hit song "99 Luftballons."
  • 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: Maren
Triple: [Maren Svarstad, givenName, Maren]
Generated description
Maren is a feminine given name of Scandinavian origin, commonly used in Norway and Denmark.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Maren
Target entity description: Maren is a feminine given name of Scandinavian origin, commonly used in Norway and Denmark.
  • A. Sheilia
    Sheilia is a feminine given name, typically considered an alternative spelling of the name Sheila.
  • B. Krista
    Krista is a feminine given name, typically considered a variant of Christina and used in various European and English-speaking countries.
  • C. Karin
    Karin is a feminine given name used in various cultures, often considered a variant of names like Karen or Katherine.
  • D. Bauline
    Bauline is a small coastal town in Newfoundland and Labrador, Canada, located on the Avalon Peninsula near St. John’s.
  • E. Nena
    Nena is a German pop singer and actress best known internationally for her 1983 hit song "99 Luftballons."
  • 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_69c687eaa7508190bb58ce2aa02039b3 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6af13151c81909b68fa6c77e1c482 completed March 27, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cbc8f1308190a4afcf10a5a7105e completed March 27, 2026, 6:26 p.m.
NEDg Description generation batch_69c6cd09753c81909df166156ffbf82a completed March 27, 2026, 6:31 p.m.
NED2 Entity disambiguation (via description) batch_69c6ce9ba47c819091496c87117e7a03 completed March 27, 2026, 6:38 p.m.
Created at: March 27, 2026, 1:56 p.m.