Triple

T12055357
Position Surface form Disambiguated ID Type / Status
Subject district of Toggenburg E287026 entity
Predicate contains P35 FINISHED
Object Mosnang
Mosnang is a Swiss municipality in the canton of St. Gallen, known for its rural character and location in the Toggenburg region.
E967316 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: Mosnang | Statement: [district of Toggenburg, contains, Mosnang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mosnang
Context triple: [district of Toggenburg, contains, Mosnang]
  • A. Mosen
    Mosen is a small Swiss village in the canton of Lucerne, situated in a rural lakeside setting in central Switzerland.
  • B. Moxhe
    Moxhe is a village in the municipality of Hannut in the province of Liège, Belgium.
  • C. Mugling
    Mugling is a small but important transport junction town in central Nepal, serving as a key crossroads between major highways connecting Kathmandu, Pokhara, and the southern plains.
  • D. Mosogar
    Mosogar is a prominent Urhobo community in Delta State, Nigeria, known as one of the major clans of the Urhobo ethnic group.
  • E. Machang
    Machang is a town and administrative district in the Malaysian state of Kelantan, known for its semi-urban character and role as a local commercial and educational hub.
  • 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: Mosnang
Triple: [district of Toggenburg, contains, Mosnang]
Generated description
Mosnang is a Swiss municipality in the canton of St. Gallen, known for its rural character and location in the Toggenburg region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mosnang
Target entity description: Mosnang is a Swiss municipality in the canton of St. Gallen, known for its rural character and location in the Toggenburg region.
  • A. Mosen
    Mosen is a small Swiss village in the canton of Lucerne, situated in a rural lakeside setting in central Switzerland.
  • B. Moxhe
    Moxhe is a village in the municipality of Hannut in the province of Liège, Belgium.
  • C. Mugling
    Mugling is a small but important transport junction town in central Nepal, serving as a key crossroads between major highways connecting Kathmandu, Pokhara, and the southern plains.
  • D. Mosogar
    Mosogar is a prominent Urhobo community in Delta State, Nigeria, known as one of the major clans of the Urhobo ethnic group.
  • E. Machang
    Machang is a town and administrative district in the Malaysian state of Kelantan, known for its semi-urban character and role as a local commercial and educational hub.
  • 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_69d6ab4780948190bdb9f7620c2ac27e completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90425258c8190ba7b3b837c439253 completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f64f40388190bfb3d2a81d5fbf5e completed May 2, 2026, 1:04 p.m.
NEDg Description generation batch_69f60335285c819089f69472b2e48130 completed May 2, 2026, 1:59 p.m.
NED2 Entity disambiguation (via description) batch_69f60410ce0481908b2deb7522a3ec00 completed May 2, 2026, 2:02 p.m.
Created at: April 8, 2026, 9:47 p.m.