Triple

T12682397
Position Surface form Disambiguated ID Type / Status
Subject Kerzers E302978 entity
Predicate hasNeighboringMunicipality P224 FINISHED
Object Fräschels
Fräschels is a small municipality in the canton of Fribourg in western Switzerland, situated near the linguistic border between German- and French-speaking regions.
 E997211 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: Fräschels | Statement: [Kerzers, hasNeighboringMunicipality, Fräschels]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Fräschels
Context triple: [Kerzers, hasNeighboringMunicipality, Fräschels]
  • A. Livarchamps
    Livarchamps is a small village in the municipality of Vaux-sur-Sûre in the Walloon region of Belgium.
  • B. Garmes
    Garmes is a surname most notably associated with Lee Garmes, an influential American cinematographer of Hollywood’s classic era.
  • C. Gressy
    Gressy is a small French commune located in the Île-de-France region, known for its residential character and proximity to Paris and Charles de Gaulle Airport.
  • D. Breuillet
    Breuillet is a commune in the Essonne department in the Île-de-France region of northern France.
  • E. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • 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: Fräschels
Triple: [Kerzers, hasNeighboringMunicipality, Fräschels]
Generated description
Fräschels is a small municipality in the canton of Fribourg in western Switzerland, situated near the linguistic border between German- and French-speaking regions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Fräschels
Target entity description: Fräschels is a small municipality in the canton of Fribourg in western Switzerland, situated near the linguistic border between German- and French-speaking regions.
  • A. Livarchamps
    Livarchamps is a small village in the municipality of Vaux-sur-Sûre in the Walloon region of Belgium.
  • B. Garmes
    Garmes is a surname most notably associated with Lee Garmes, an influential American cinematographer of Hollywood’s classic era.
  • C. Gressy
    Gressy is a small French commune located in the Île-de-France region, known for its residential character and proximity to Paris and Charles de Gaulle Airport.
  • D. Breuillet
    Breuillet is a commune in the Essonne department in the Île-de-France region of northern France.
  • E. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • 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_69f67323a724819092425cdb3a070b96 completed May 2, 2026, 9:56 p.m.
Created at: April 9, 2026, 5:21 p.m.