Triple

T24743
Position Surface form Disambiguated ID Type / Status
Subject Cambridge, England E492 entity
Predicate hasTwinTown P919 FINISHED
Object Székesfehérvár
Székesfehérvár is a historic city in central Hungary that served as a medieval royal seat and coronation site for Hungarian kings.
 E3113 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: Székesfehérvár | Statement: [Cambridge, England, hasTwinTown, Székesfehérvár]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Székesfehérvár
Context triple: [Cambridge, England, hasTwinTown, Székesfehérvár]
  • A. Chemnitz
    Chemnitz is a city in eastern Germany known for its industrial heritage and post-reunification urban redevelopment.
  • B. Vichy
    Vichy is a spa town in central France renowned for its thermal springs, health resorts, and role as the seat of the World War II Vichy regime.
  • C. Gori
    Gori is a city in central Georgia best known as the birthplace of Soviet leader Joseph Stalin.
  • D. Roma
    The Roma are a traditionally nomadic ethnic group originating from the Indian subcontinent and living mainly in Europe, long subjected to persecution and discrimination, including mass murder during the Holocaust.
  • E. Geneva
    Geneva is a major Swiss city on Lake Geneva known for hosting numerous international organizations, including United Nations agencies and the Red Cross.
  • 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: Székesfehérvár
Triple: [Cambridge, England, hasTwinTown, Székesfehérvár]
Generated description
Székesfehérvár is a historic city in central Hungary that served as a medieval royal seat and coronation site for Hungarian kings.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Székesfehérvár
Target entity description: Székesfehérvár is a historic city in central Hungary that served as a medieval royal seat and coronation site for Hungarian kings.
  • A. Chemnitz
    Chemnitz is a city in eastern Germany known for its industrial heritage and post-reunification urban redevelopment.
  • B. Vichy
    Vichy is a spa town in central France renowned for its thermal springs, health resorts, and role as the seat of the World War II Vichy regime.
  • C. Gori
    Gori is a city in central Georgia best known as the birthplace of Soviet leader Joseph Stalin.
  • D. Roma
    The Roma are a traditionally nomadic ethnic group originating from the Indian subcontinent and living mainly in Europe, long subjected to persecution and discrimination, including mass murder during the Holocaust.
  • E. Geneva
    Geneva is a major Swiss city on Lake Geneva known for hosting numerous international organizations, including United Nations agencies and the Red Cross.
  • 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_69a243b4ac2c8190b93c303df797b7b2 completed Feb. 28, 2026, 1:24 a.m.
NER Named-entity recognition batch_69a2466d166881908bd8513c8d09fe8d completed Feb. 28, 2026, 1:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69a24e59b35c8190a192ed9095a8756d completed Feb. 28, 2026, 2:09 a.m.
NEDg Description generation batch_69a24edf06688190963f6812d173d56e completed Feb. 28, 2026, 2:11 a.m.
NED2 Entity disambiguation (via description) batch_69a24fec71908190813a1e322bbbdbb6 completed Feb. 28, 2026, 2:16 a.m.
Created at: Feb. 28, 2026, 1:34 a.m.