Triple

T17367904
Position Surface form Disambiguated ID Type / Status
Subject Visp District E422231 entity
Predicate contains P35 FINISHED
Object Zeneggen — NE ONDG

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: Zeneggen | Statement: [Visp District, contains, Zeneggen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zeneggen
Context triple: [Visp District, contains, Zeneggen]
  • A. Zegen
    Zegen is a surname most notably associated with American actor Michael Zegen, known for his roles in television and film.
  • B. Zwenkau
    Zwenkau is a small town in the Free State of Saxony in eastern Germany, situated near Leipzig and known for its proximity to former lignite mining areas now being transformed into lake landscapes.
  • C. Zannanza
    Zannanza was a Hittite prince, best known for his ill-fated journey to marry the Egyptian widow-queen that sparked a major diplomatic crisis between the Hittite and Egyptian empires.
  • D. Flerzheim
    Flerzheim is a village and district of the town of Rheinbach in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
  • E. Zvenigora
    Zvenigora is a 1928 Soviet silent film by Ukrainian director Alexander Dovzhenko, celebrated for its poetic, avant-garde style and exploration of Ukrainian history and folklore.
  • 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: Zeneggen
Triple: [Visp District, contains, Zeneggen]
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zeneggen
Target entity description: Zeneggen is a small Swiss mountain municipality in the canton of Valais, known for its alpine scenery and traditional rural character.
  • A. Zegen
    Zegen is a surname most notably associated with American actor Michael Zegen, known for his roles in television and film.
  • B. Zwenkau
    Zwenkau is a small town in the Free State of Saxony in eastern Germany, situated near Leipzig and known for its proximity to former lignite mining areas now being transformed into lake landscapes.
  • C. Zannanza
    Zannanza was a Hittite prince, best known for his ill-fated journey to marry the Egyptian widow-queen that sparked a major diplomatic crisis between the Hittite and Egyptian empires.
  • D. Flerzheim
    Flerzheim is a village and district of the town of Rheinbach in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
  • E. Zvenigora
    Zvenigora is a 1928 Soviet silent film by Ukrainian director Alexander Dovzhenko, celebrated for its poetic, avant-garde style and exploration of Ukrainian history and folklore.
  • F. None of above. chosen

Provenance (4 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_69d889d6535c81908be333c01deaec4e completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a661fc08190a4c386125bddb16b completed April 19, 2026, 2:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a019566da6c819083b59e0911d02bd5 completed May 11, 2026, 8:37 a.m.
NEDg Description generation batch_6a01962ae4848190b2aad8e19bf6522f in_progress May 11, 2026, 8:41 a.m.
Created at: April 10, 2026, 5:44 a.m.