Triple

T15968777
Position Surface form Disambiguated ID Type / Status
Subject Spenge E387265 entity
Predicate river P165 FINISHED
Object Warmbecke
Warmbecke is a small river in North Rhine-Westphalia, Germany, associated with the town of Spenge.
E1186046 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: Warmbecke | Statement: [Spenge, river, Warmbecke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Warmbecke
Context triple: [Spenge, river, Warmbecke]
  • A. Warmbrodt
    Warmbrodt is a surname most notably associated with Sara Sothern, the American stage actress and mother of film star Elizabeth Taylor.
  • B. Wieck
    Wieck is a German surname most notably associated with Friedrich Wieck, the influential 19th-century piano teacher and father of composer Clara Schumann.
  • C. Weiherhammer
    Weiherhammer is a small municipality in the Upper Palatinate region of Bavaria, Germany, known for its rural character and local industry.
  • D. Schelle
    Schelle is a municipality in the Belgian province of Antwerp, situated along the Rupel River.
  • E. Hetzel
    Hetzel was a prominent 19th-century French publisher best known for publishing major literary works, including those of Victor Hugo and Jules Verne.
  • 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: Warmbecke
Triple: [Spenge, river, Warmbecke]
Generated description
Warmbecke is a small river in North Rhine-Westphalia, Germany, associated with the town of Spenge.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Warmbecke
Target entity description: Warmbecke is a small river in North Rhine-Westphalia, Germany, associated with the town of Spenge.
  • A. Warmbrodt
    Warmbrodt is a surname most notably associated with Sara Sothern, the American stage actress and mother of film star Elizabeth Taylor.
  • B. Wieck
    Wieck is a German surname most notably associated with Friedrich Wieck, the influential 19th-century piano teacher and father of composer Clara Schumann.
  • C. Weiherhammer
    Weiherhammer is a small municipality in the Upper Palatinate region of Bavaria, Germany, known for its rural character and local industry.
  • D. Schelle
    Schelle is a municipality in the Belgian province of Antwerp, situated along the Rupel River.
  • E. Hetzel
    Hetzel was a prominent 19th-century French publisher best known for publishing major literary works, including those of Victor Hugo and Jules Verne.
  • 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_69d86da94ccc819083d187f5dc6a123e completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1572847f08190830e30125e829766 completed April 16, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffbe87149081909ac6129126f597c2 completed May 9, 2026, 11:08 p.m.
NEDg Description generation batch_69ffbf3e80b08190899262a9d03c0e93 completed May 9, 2026, 11:11 p.m.
NED2 Entity disambiguation (via description) batch_69ffbfc0d1548190b7d2e9e10e837f0b completed May 9, 2026, 11:14 p.m.
Created at: April 10, 2026, 4:54 a.m.