Triple

T17147941
Position Surface form Disambiguated ID Type / Status
Subject Aulendorf–Kißlegg railway E416142 entity
Predicate endPoint P390 FINISHED
Object Kißlegg
Kißlegg is a small town in the Ravensburg district of Baden-Württemberg, Germany, known for its historic castles and location in the scenic Allgäu region.
 E1251991 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: Kißlegg | Statement: [Aulendorf–Kißlegg railway, endPoint, Kißlegg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kißlegg
Context triple: [Aulendorf–Kißlegg railway, endPoint, Kißlegg]
  • A. Tihany
    Tihany is a historic village on the northern shore of Lake Balaton in Hungary, renowned for its Benedictine abbey, scenic peninsula, and traditional architecture.
  • B. Kékes
    Kékes is the highest peak in Hungary, known for its popular hiking trails and ski resort facilities.
  • C. Kazincbarcika
    Kazincbarcika is an industrial town in northeastern Hungary, located in Borsod-Abaúj-Zemplén County.
  • D. Villány
    Villány is a small town in southern Hungary renowned as one of the country’s premier wine regions, especially famous for its red wines.
  • E. Hollókő
    Hollókő is a UNESCO World Heritage-listed Hungarian village renowned for its well-preserved traditional Palóc architecture and living rural culture.
  • 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: Kißlegg
Triple: [Aulendorf–Kißlegg railway, endPoint, Kißlegg]
Generated description
Kißlegg is a small town in the Ravensburg district of Baden-Württemberg, Germany, known for its historic castles and location in the scenic Allgäu region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kißlegg
Target entity description: Kißlegg is a small town in the Ravensburg district of Baden-Württemberg, Germany, known for its historic castles and location in the scenic Allgäu region.
  • A. Tihany
    Tihany is a historic village on the northern shore of Lake Balaton in Hungary, renowned for its Benedictine abbey, scenic peninsula, and traditional architecture.
  • B. Kékes
    Kékes is the highest peak in Hungary, known for its popular hiking trails and ski resort facilities.
  • C. Kazincbarcika
    Kazincbarcika is an industrial town in northeastern Hungary, located in Borsod-Abaúj-Zemplén County.
  • D. Villány
    Villány is a small town in southern Hungary renowned as one of the country’s premier wine regions, especially famous for its red wines.
  • E. Hollókő
    Hollókő is a UNESCO World Heritage-listed Hungarian village renowned for its well-preserved traditional Palóc architecture and living rural culture.
  • 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_69d886d15af4819092f92f8a129763e6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f404f0e88190b7ac9ac523fdc7da completed April 18, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01415b1d7c81908d000b0362042687 completed May 11, 2026, 2:39 a.m.
NEDg Description generation batch_6a0141b73e008190be8aa85dec1ba517 completed May 11, 2026, 2:40 a.m.
NED2 Entity disambiguation (via description) batch_6a01421d159c819096efc46fa08a48b9 completed May 11, 2026, 2:42 a.m.
Created at: April 10, 2026, 5:36 a.m.