Triple

T2906306
Position Surface form Disambiguated ID Type / Status
Subject High Wycombe E62771 entity
Predicate hasTwinTown P919 FINISHED
Object Kelkheim
Kelkheim is a town in the Main-Taunus district of Hesse, Germany, known for its furniture industry and proximity to Frankfurt.
E315641 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: Kelkheim | Statement: [High Wycombe, hasTwinTown, Kelkheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kelkheim
Context triple: [High Wycombe, hasTwinTown, Kelkheim]
  • A. Rheydt
    Rheydt is a district of the German city of Mönchengladbach in North Rhine-Westphalia, historically an independent town in the Rhineland.
  • B. Kleve
    Kleve is a historic town in western Germany near the Dutch border, known for its medieval castle and role as the former capital of the Duchy of Cleves.
  • C. Schlettstadt
    Schlettstadt, now known as Sélestat, is a historic town in the Alsace region of northeastern France noted for its medieval architecture and humanist heritage.
  • D. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • E. Lahnstein
    Lahnstein is a historic town in western Germany, located on the Rhine River in the state of Rhineland-Palatinate.
  • 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: Kelkheim
Triple: [High Wycombe, hasTwinTown, Kelkheim]
Generated description
Kelkheim is a town in the Main-Taunus district of Hesse, Germany, known for its furniture industry and proximity to Frankfurt.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kelkheim
Target entity description: Kelkheim is a town in the Main-Taunus district of Hesse, Germany, known for its furniture industry and proximity to Frankfurt.
  • A. Rheydt
    Rheydt is a district of the German city of Mönchengladbach in North Rhine-Westphalia, historically an independent town in the Rhineland.
  • B. Kleve
    Kleve is a historic town in western Germany near the Dutch border, known for its medieval castle and role as the former capital of the Duchy of Cleves.
  • C. Schlettstadt
    Schlettstadt, now known as Sélestat, is a historic town in the Alsace region of northeastern France noted for its medieval architecture and humanist heritage.
  • D. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • E. Lahnstein
    Lahnstein is a historic town in western Germany, located on the Rhine River in the state of Rhineland-Palatinate.
  • 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_69ab4c3e070c8190b78d3d2c005876dd completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abe0cee7988190875665145c3cd605 completed March 7, 2026, 8:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69b108ceccec8190807a95c29cdfb76e completed March 11, 2026, 6:16 a.m.
NEDg Description generation batch_69b109aca8008190aa34902fb63fb1a3 completed March 11, 2026, 6:20 a.m.
NED2 Entity disambiguation (via description) batch_69b10a5da7d08190967750728135ab68 completed March 11, 2026, 6:23 a.m.
Created at: March 6, 2026, 10:11 p.m.