Triple

T12282749
Position Surface form Disambiguated ID Type / Status
Subject Gaussian process E292752 entity
Predicate alsoKnownAs P39 FINISHED
Object GP
A Gaussian process (GP) is a probabilistic model that defines a distribution over functions, widely used in machine learning and statistics for regression, classification, and Bayesian optimization.
 E974247 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: GP | Statement: [Gaussian process, alsoKnownAs, GP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: GP
Context triple: [Gaussian process, alsoKnownAs, GP]
  • A. GP
    GP is the vehicle registration code used on license plates for the German town and district of Göppingen in the state of Baden-Württemberg.
  • B. GP
    GP is the 1973 debut solo album by American singer-songwriter Gram Parsons, often hailed as a landmark recording in the development of country rock.
  • C. GP
    GP is the two-letter ISO 3166-1 alpha-2 country code assigned to Guadeloupe.
  • D. GW
    GW (Gesamtkatalog der Wiegendrucke) is a comprehensive scholarly catalog of incunabula, documenting books printed in Europe before 1501.
  • E. GPC
    GPC is the commonly used acronym for the Green Party of Canada, a federal political party focused on environmentalism and social justice.
  • 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: GP
Triple: [Gaussian process, alsoKnownAs, GP]
Generated description
A Gaussian process (GP) is a probabilistic model that defines a distribution over functions, widely used in machine learning and statistics for regression, classification, and Bayesian optimization.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: GP
Target entity description: A Gaussian process (GP) is a probabilistic model that defines a distribution over functions, widely used in machine learning and statistics for regression, classification, and Bayesian optimization.
  • A. GP
    GP is the two-letter ISO 3166-1 alpha-2 country code assigned to Guadeloupe.
  • B. GP
    GP is the vehicle registration code used on license plates for the German town and district of Göppingen in the state of Baden-Württemberg.
  • C. GP
    GP is the 1973 debut solo album by American singer-songwriter Gram Parsons, often hailed as a landmark recording in the development of country rock.
  • D. GW
    GW (Gesamtkatalog der Wiegendrucke) is a comprehensive scholarly catalog of incunabula, documenting books printed in Europe before 1501.
  • E. GPC
    GPC is the commonly used acronym for the Green Party of Canada, a federal political party focused on environmentalism and social justice.
  • 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_69d6ab690ad081908c0ed3870ec82d53 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cf2b09c81908a11581d33f65be0 completed April 10, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e70dec8819098199fbb54d888c1 completed May 2, 2026, 3:55 p.m.
NEDg Description generation batch_69f61f5bc1fc8190af9d74acc307ebe1 completed May 2, 2026, 3:59 p.m.
NED2 Entity disambiguation (via description) batch_69f6203ef5008190af9103460b096cff completed May 2, 2026, 4:03 p.m.
Created at: April 8, 2026, 9:52 p.m.