Triple

T9218414
Position Surface form Disambiguated ID Type / Status
Subject Luxembourg Province E221297 entity
Predicate containsTown P847 FINISHED
Object Nassogne
Nassogne is a rural municipality and village in the Ardennes region of Belgium’s Luxembourg Province, known for its forests and traditional countryside.
E814654 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: Nassogne | Statement: [Luxembourg Province, containsTown, Nassogne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nassogne
Context triple: [Luxembourg Province, containsTown, Nassogne]
  • A. Randogne
    Randogne is a former Swiss municipality in the canton of Valais that later became part of the resort area of Crans-Montana.
  • B. Nançon River
    The Nançon River is a small watercourse in northwestern France that flows through the historic town of Fougères in the Ille-et-Vilaine department of Brittany.
  • C. Sauldre
    Sauldre is a river in central France that flows through the Cher department and is a tributary of the larger Sauldre river system.
  • D. Riorges
    Riorges is a commune in central France, near Roanne in the Loire department, known for its residential character and local cultural life.
  • E. Ouvèze River
    The Ouvèze River is a river in southeastern France that flows through the Drôme and Vaucluse departments before joining the Rhône.
  • 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: Nassogne
Triple: [Luxembourg Province, containsTown, Nassogne]
Generated description
Nassogne is a rural municipality and village in the Ardennes region of Belgium’s Luxembourg Province, known for its forests and traditional countryside.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nassogne
Target entity description: Nassogne is a rural municipality and village in the Ardennes region of Belgium’s Luxembourg Province, known for its forests and traditional countryside.
  • A. Randogne
    Randogne is a former Swiss municipality in the canton of Valais that later became part of the resort area of Crans-Montana.
  • B. Nançon River
    The Nançon River is a small watercourse in northwestern France that flows through the historic town of Fougères in the Ille-et-Vilaine department of Brittany.
  • C. Sauldre
    Sauldre is a river in central France that flows through the Cher department and is a tributary of the larger Sauldre river system.
  • D. Riorges
    Riorges is a commune in central France, near Roanne in the Loire department, known for its residential character and local cultural life.
  • E. Ouvèze River
    The Ouvèze River is a river in southeastern France that flows through the Drôme and Vaucluse departments before joining the Rhône.
  • 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_69ca83eae42c8190a0ea9e040710a277 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccda730f688190b64b2cc8c4898ac3 completed April 1, 2026, 8:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69d190bef8548190a058e6014ff6690c completed April 4, 2026, 10:29 p.m.
NEDg Description generation batch_69d19327f0b481908be85bcb0deccb46 completed April 4, 2026, 10:39 p.m.
NED2 Entity disambiguation (via description) batch_69d193fac390819092dd913dc78e2841 completed April 4, 2026, 10:43 p.m.
Created at: March 30, 2026, 7:27 p.m.