Triple

T12682365
Position Surface form Disambiguated ID Type / Status
Subject Ins E302977 entity
Predicate hasNeighboringMunicipality P224 FINISHED
Object Tschugg
Tschugg is a small municipality in the canton of Bern, Switzerland, known for its rural setting near Lake Biel and its historic manor house that now serves as a neurological clinic.
E997754 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: Tschugg | Statement: [Ins, hasNeighboringMunicipality, Tschugg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tschugg
Context triple: [Ins, hasNeighboringMunicipality, Tschugg]
  • A. Kogon
    Kogon is a small city in Uzbekistan known for its location near the historic center of Bukhara and its role as a local transport and industrial hub.
  • B. Tukker
    Tukker is a given name or surname that functions as a variant spelling of the name Tucker.
  • C. Chivv
    Chivv is a Dutch rapper and singer known for his work in the hip-hop and Afrobeat scenes, including collaborations with international artists.
  • D. Cheget
    Cheget is a small mountain village and ski resort in Russia’s Caucasus region, serving as a popular base for visitors to Mount Elbrus.
  • E. Ropscha
    Ropscha is a rural locality in Leningrad Oblast, Russia, historically known for its imperial estate associated with the Russian royal family.
  • 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: Tschugg
Triple: [Ins, hasNeighboringMunicipality, Tschugg]
Generated description
Tschugg is a small municipality in the canton of Bern, Switzerland, known for its rural setting near Lake Biel and its historic manor house that now serves as a neurological clinic.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tschugg
Target entity description: Tschugg is a small municipality in the canton of Bern, Switzerland, known for its rural setting near Lake Biel and its historic manor house that now serves as a neurological clinic.
  • A. Kogon
    Kogon is a small city in Uzbekistan known for its location near the historic center of Bukhara and its role as a local transport and industrial hub.
  • B. Tukker
    Tukker is a given name or surname that functions as a variant spelling of the name Tucker.
  • C. Chivv
    Chivv is a Dutch rapper and singer known for his work in the hip-hop and Afrobeat scenes, including collaborations with international artists.
  • D. Cheget
    Cheget is a small mountain village and ski resort in Russia’s Caucasus region, serving as a popular base for visitors to Mount Elbrus.
  • E. Ropscha
    Ropscha is a rural locality in Leningrad Oblast, Russia, historically known for its imperial estate associated with the Russian royal family.
  • 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_69d7bdee64a08190801c6d470aefd723 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961d68358819095bdaab8adf1dcf0 completed April 10, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671a733a48190b55d296573c86eaf completed May 2, 2026, 9:50 p.m.
NEDg Description generation batch_69f67285019c8190be831d3f72cf121f completed May 2, 2026, 9:54 p.m.
NED2 Entity disambiguation (via description) batch_69f6732ea7408190a95f0a5f983dfdb7 completed May 2, 2026, 9:57 p.m.
Created at: April 9, 2026, 5:21 p.m.