Triple

T1213574
Position Surface form Disambiguated ID Type / Status
Subject University of Königsberg E26057 entity
Predicate alternativeName P39 FINISHED
Object Albertina
Albertina was the historic University of Königsberg, a prominent Prussian center of learning and research founded in the 16th century.
 E143258 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: Albertina | Statement: [University of Königsberg, alternativeName, Albertina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Albertina
Context triple: [University of Königsberg, alternativeName, Albertina]
  • A. Antoinette
    Antoinette is the birth name of Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
  • B. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • C. Bettina
    Bettina is a feminine given name of Hebrew origin, often considered a diminutive of Elisabeth or Benedetta and used in various European languages.
  • D. Ricarda
    Ricarda is a feminine given name, primarily used in German- and Spanish-speaking countries, derived from the male name Richard.
  • E. Agatha van Pruyssen
    Agatha van Pruyssen was the wife of Dutch Golden Age painter Carel Fabritius, known for her connection to the artist’s brief but influential life and career.
  • 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: Albertina
Triple: [University of Königsberg, alternativeName, Albertina]
Generated description
Albertina was the historic University of Königsberg, a prominent Prussian center of learning and research founded in the 16th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Albertina
Target entity description: Albertina was the historic University of Königsberg, a prominent Prussian center of learning and research founded in the 16th century.
  • A. Antoinette
    Antoinette is the birth name of Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
  • B. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • C. Bettina
    Bettina is a feminine given name of Hebrew origin, often considered a diminutive of Elisabeth or Benedetta and used in various European languages.
  • D. Ricarda
    Ricarda is a feminine given name, primarily used in German- and Spanish-speaking countries, derived from the male name Richard.
  • E. Agatha van Pruyssen
    Agatha van Pruyssen was the wife of Dutch Golden Age painter Carel Fabritius, known for her connection to the artist’s brief but influential life and career.
  • 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_69a4948331fc8190b531ac9bec71c491 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be024e448190ba263a0cc5cc9cd5 completed March 1, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac93bcdbbc8190a5eb1f4285faa8d4 completed March 7, 2026, 9:08 p.m.
NEDg Description generation batch_69ac9453f4488190a13ebabf3c8e07a5 completed March 7, 2026, 9:10 p.m.
NED2 Entity disambiguation (via description) batch_69ac952f74d48190b075919e0acd513d completed March 7, 2026, 9:14 p.m.
Created at: March 1, 2026, 7:46 p.m.