Triple

T15369546
Position Surface form Disambiguated ID Type / Status
Subject Radolfzell E367506 entity
Predicate hasTwinTown P919 FINISHED
Object Amriswil
Amriswil is a small Swiss town in the canton of Thurgau known for its residential character and local industry.
E1191653 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: Amriswil | Statement: [Radolfzell, hasTwinTown, Amriswil]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amriswil
Context triple: [Radolfzell, hasTwinTown, Amriswil]
  • A. Attiswil
    Attiswil is a municipality in the canton of Bern in Switzerland, located in the Oberaargau region.
  • B. Waldegg
    Waldegg is a locality in Switzerland situated along the route of the A3 motorway.
  • C. Bonstetten
    Bonstetten is a small municipality in the Swabian region of Bavaria in southern Germany.
  • D. Kesswil
    Kesswil is a small Swiss village on the shores of Lake Constance, best known as the birthplace of the influential psychiatrist and psychoanalyst Carl Gustav Jung.
  • E. Ramiswil
    Ramiswil is a small rural municipality in the canton of Solothurn in northwestern Switzerland, known for its scenic Jura landscape and agricultural character.
  • 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: Amriswil
Triple: [Radolfzell, hasTwinTown, Amriswil]
Generated description
Amriswil is a small Swiss town in the canton of Thurgau known for its residential character and local industry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Amriswil
Target entity description: Amriswil is a small Swiss town in the canton of Thurgau known for its residential character and local industry.
  • A. Attiswil
    Attiswil is a municipality in the canton of Bern in Switzerland, located in the Oberaargau region.
  • B. Waldegg
    Waldegg is a locality in Switzerland situated along the route of the A3 motorway.
  • C. Bonstetten
    Bonstetten is a small municipality in the Swabian region of Bavaria in southern Germany.
  • D. Kesswil
    Kesswil is a small Swiss village on the shores of Lake Constance, best known as the birthplace of the influential psychiatrist and psychoanalyst Carl Gustav Jung.
  • E. Ramiswil
    Ramiswil is a small rural municipality in the canton of Solothurn in northwestern Switzerland, known for its scenic Jura landscape and agricultural character.
  • 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_69d85a1483788190ad93c2748e8af34b completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e4b88a881909f9575c02aed287d completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbba9fb08190b800af317f0c9abf completed May 10, 2026, 1:13 a.m.
NEDg Description generation batch_69ffddad79d0819085d4131eca0bda02 completed May 10, 2026, 1:21 a.m.
NED2 Entity disambiguation (via description) batch_69ffde14228c81909e61814cbf44e013 completed May 10, 2026, 1:23 a.m.
Created at: April 10, 2026, 3:18 a.m.