Triple

T4195619
Position Surface form Disambiguated ID Type / Status
Subject Karl Bühler E89146 entity
Predicate placeOfBirth P1 FINISHED
Object Meckesheim
Meckesheim is a small municipality in southwestern Germany’s Rhine-Neckar region, known as a rural community with historical roots in Baden-Württemberg.
E423444 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: Meckesheim | Statement: [Karl Bühler, placeOfBirth, Meckesheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meckesheim
Context triple: [Karl Bühler, placeOfBirth, Meckesheim]
  • A. Mergentheim
    Mergentheim is a historic town in southern Germany best known as the former main seat of the Teutonic Order and for its well-preserved medieval and baroque architecture.
  • B. Igersheim
    Igersheim is a small municipality in the Main-Tauber district of Baden-Württemberg in southern Germany.
  • C. Rheydt
    Rheydt is a district of the German city of Mönchengladbach in North Rhine-Westphalia, historically an independent town in the Rhineland.
  • D. Gernsbach
    Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting along the Murg River.
  • E. Kelkheim
    Kelkheim is a town in the Main-Taunus district of Hesse, Germany, known for its furniture industry and proximity to Frankfurt.
  • 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: Meckesheim
Triple: [Karl Bühler, placeOfBirth, Meckesheim]
Generated description
Meckesheim is a small municipality in southwestern Germany’s Rhine-Neckar region, known as a rural community with historical roots in Baden-Württemberg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Meckesheim
Target entity description: Meckesheim is a small municipality in southwestern Germany’s Rhine-Neckar region, known as a rural community with historical roots in Baden-Württemberg.
  • A. Mergentheim
    Mergentheim is a historic town in southern Germany best known as the former main seat of the Teutonic Order and for its well-preserved medieval and baroque architecture.
  • B. Igersheim
    Igersheim is a small municipality in the Main-Tauber district of Baden-Württemberg in southern Germany.
  • C. Rheydt
    Rheydt is a district of the German city of Mönchengladbach in North Rhine-Westphalia, historically an independent town in the Rhineland.
  • D. Gernsbach
    Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting along the Murg River.
  • E. Kelkheim
    Kelkheim is a town in the Main-Taunus district of Hesse, Germany, known for its furniture industry and proximity to Frankfurt.
  • 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_69aed9569a4481908b6c1fcec2a11e21 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af035e87148190a0f0bf48b813ffaa completed March 9, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5a84d00b8819082982c4d229c450e completed March 14, 2026, 6:26 p.m.
NEDg Description generation batch_69b5a983cfd88190b702c420d6dbc201 completed March 14, 2026, 6:31 p.m.
NED2 Entity disambiguation (via description) batch_69b5aa00bcd88190ad2fba212861c712 completed March 14, 2026, 6:33 p.m.
Created at: March 9, 2026, 3:46 p.m.