Triple

T6035127
Position Surface form Disambiguated ID Type / Status
Subject Tilburg E134398 entity
Predicate hasNeighbourhood P4813 FINISHED
Object Korvel
Korvel is a residential neighborhood in the Dutch city of Tilburg, known for its mix of urban housing, local shops, and multicultural character.
E565104 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: Korvel | Statement: [Tilburg, hasNeighbourhood, Korvel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Korvel
Context triple: [Tilburg, hasNeighbourhood, Korvel]
  • A. Kelmis
    Kelmis is a municipality in eastern Belgium located in the country's German-speaking region, known for its historical zinc mining industry and borderland character near Germany and the Netherlands.
  • B. Konerko
    Konerko is the surname of Paul Konerko, a former Major League Baseball first baseman best known for his long tenure and leadership with the Chicago White Sox.
  • C. Kurux
    Kurux is a Dravidian language spoken primarily by the Kurukh (Oraon) people in eastern and central India and parts of Bangladesh.
  • D. Krakhuna
    Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
  • E. Kaiten
    Kaiten was a Japanese warship that took part in the late-19th-century Boshin War naval engagements, including the Battle of Hakodate.
  • 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: Korvel
Triple: [Tilburg, hasNeighbourhood, Korvel]
Generated description
Korvel is a residential neighborhood in the Dutch city of Tilburg, known for its mix of urban housing, local shops, and multicultural character.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Korvel
Target entity description: Korvel is a residential neighborhood in the Dutch city of Tilburg, known for its mix of urban housing, local shops, and multicultural character.
  • A. Kelmis
    Kelmis is a municipality in eastern Belgium located in the country's German-speaking region, known for its historical zinc mining industry and borderland character near Germany and the Netherlands.
  • B. Konerko
    Konerko is the surname of Paul Konerko, a former Major League Baseball first baseman best known for his long tenure and leadership with the Chicago White Sox.
  • C. Kurux
    Kurux is a Dravidian language spoken primarily by the Kurukh (Oraon) people in eastern and central India and parts of Bangladesh.
  • D. Krakhuna
    Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
  • E. Kaiten
    Kaiten was a Japanese warship that took part in the late-19th-century Boshin War naval engagements, including the Battle of Hakodate.
  • 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_69c00875db5c819099dd5bb833ec43c2 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c056b33a7c8190ad6282286199b192 completed March 22, 2026, 8:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c11388aec881908408d5844c96ea2d completed March 23, 2026, 10:18 a.m.
NEDg Description generation batch_69c11689c0788190847435b526572edc completed March 23, 2026, 10:31 a.m.
NED2 Entity disambiguation (via description) batch_69c116eb349c81908cad0bf5ccc458bc completed March 23, 2026, 10:33 a.m.
Created at: March 22, 2026, 4:08 p.m.