Triple

T22600602
Position Surface form Disambiguated ID Type / Status
Subject Münster-Geschinen E574805 entity
Predicate hasPart P35 FINISHED
Object Geschinen
Geschinen is a small Swiss village in the canton of Valais, known for its traditional alpine character and scenic mountain surroundings.
 E1546076 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: Geschinen | Statement: [Münster-Geschinen, hasPart, Geschinen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Geschinen
Context triple: [Münster-Geschinen, hasPart, Geschinen]
  • A. Seewald
    Seewald is a rural municipality in the Black Forest region of Baden-Württemberg, Germany, known for its forests, lakes, and outdoor recreation.
  • B. Burgäschi
    Burgäschi is a small Swiss locality known for its proximity to Lake Burgäschi, a scenic lake popular for recreation and nature activities.
  • C. Genthod
    Genthod is a small lakeside municipality in western Switzerland, situated on the shores of Lake Geneva near the city of Geneva.
  • D. Schlarigna
    Schlarigna is the Romansh name for the Swiss alpine village and resort town of Celerina in the Upper Engadine region of Graubünden.
  • E. Murino
    Murino is a rapidly growing suburban town on the outskirts of Saint Petersburg in northwestern Russia.
  • 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: Geschinen
Triple: [Münster-Geschinen, hasPart, Geschinen]
Generated description
Geschinen is a small Swiss village in the canton of Valais, known for its traditional alpine character and scenic mountain surroundings.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Geschinen
Target entity description: Geschinen is a small Swiss village in the canton of Valais, known for its traditional alpine character and scenic mountain surroundings.
  • A. Seewald
    Seewald is a rural municipality in the Black Forest region of Baden-Württemberg, Germany, known for its forests, lakes, and outdoor recreation.
  • B. Burgäschi
    Burgäschi is a small Swiss locality known for its proximity to Lake Burgäschi, a scenic lake popular for recreation and nature activities.
  • C. Genthod
    Genthod is a small lakeside municipality in western Switzerland, situated on the shores of Lake Geneva near the city of Geneva.
  • D. Schlarigna
    Schlarigna is the Romansh name for the Swiss alpine village and resort town of Celerina in the Upper Engadine region of Graubünden.
  • E. Murino
    Murino is a rapidly growing suburban town on the outskirts of Saint Petersburg in northwestern Russia.
  • 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_69e245bc11308190b69d794d5d1e0bb6 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1626c6ce08190b991e89b12c67a5a completed April 29, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b4df558e8819096fc5446c268160e completed May 18, 2026, 5:35 p.m.
NEDg Description generation batch_6a0b50a38c6c8190bc8f9b9390bddbea completed May 18, 2026, 5:47 p.m.
NED2 Entity disambiguation (via description) batch_6a0b5186819081909309126fa9169677 completed May 18, 2026, 5:51 p.m.
Created at: April 17, 2026, 2:50 p.m.