Triple

T15968909
Position Surface form Disambiguated ID Type / Status
Subject Löhne E387268 entity
Predicate subdivision P747 FINISHED
Object Mennighüffen
Mennighüffen is a district within the town of Löhne in North Rhine-Westphalia, Germany.
E1189546 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: Mennighüffen | Statement: [Löhne, subdivision, Mennighüffen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mennighüffen
Context triple: [Löhne, subdivision, Mennighüffen]
  • A. Bammental
    Bammental is a small municipality in southwestern Germany’s Rhine-Neckar region, known for its scenic location in the Elsenz valley near Heidelberg.
  • B. Hürnbach
    Hürnbach is a small stream in Switzerland that serves as a tributary of the river Wigger.
  • C. Warth-Schröcken
    Warth-Schröcken is a small alpine ski resort village in the Austrian state of Vorarlberg, known for its reliable snowfall and access to the Arlberg ski area.
  • D. Rolandseck
    Rolandseck is a district of Remagen in Rhineland-Palatinate, Germany, known for its scenic location on the Rhine and its historic railway station and cultural venues.
  • E. La Bresse-Hohneck
    La Bresse-Hohneck is a major ski resort in the Vosges Mountains of northeastern France, known for its extensive network of alpine ski runs and family-friendly winter sports facilities.
  • 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: Mennighüffen
Triple: [Löhne, subdivision, Mennighüffen]
Generated description
Mennighüffen is a district within the town of Löhne in North Rhine-Westphalia, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mennighüffen
Target entity description: Mennighüffen is a district within the town of Löhne in North Rhine-Westphalia, Germany.
  • A. Bammental
    Bammental is a small municipality in southwestern Germany’s Rhine-Neckar region, known for its scenic location in the Elsenz valley near Heidelberg.
  • B. Hürnbach
    Hürnbach is a small stream in Switzerland that serves as a tributary of the river Wigger.
  • C. Warth-Schröcken
    Warth-Schröcken is a small alpine ski resort village in the Austrian state of Vorarlberg, known for its reliable snowfall and access to the Arlberg ski area.
  • D. Rolandseck
    Rolandseck is a district of Remagen in Rhineland-Palatinate, Germany, known for its scenic location on the Rhine and its historic railway station and cultural venues.
  • E. La Bresse-Hohneck
    La Bresse-Hohneck is a major ski resort in the Vosges Mountains of northeastern France, known for its extensive network of alpine ski runs and family-friendly winter sports facilities.
  • 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_69ffcf1893388190800f013fab415ae7 completed May 10, 2026, 12:19 a.m.
NEDg Description generation batch_69ffd049952081909221df73d3555557 completed May 10, 2026, 12:24 a.m.
NED2 Entity disambiguation (via description) batch_69ffd10ab484819089cd94ef07cb8de5 completed May 10, 2026, 12:27 a.m.
Created at: April 10, 2026, 4:54 a.m.