Triple

T13989646
Position Surface form Disambiguated ID Type / Status
Subject Florenville E336534 entity
Predicate hasSubdivision P747 FINISHED
Object Muno
Muno is a village in the municipality of Florenville in the Wallonia region of southern Belgium.
E1073510 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: Muno | Statement: [Florenville, hasSubdivision, Muno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Muno
Context triple: [Florenville, hasSubdivision, Muno]
  • A. Mook
    Mook is a village in the Dutch province of Limburg, known for its scenic location along the Maas River near the German border.
  • B. Mook
    Mook is a surname most notably associated with Robby Mook, an American political strategist and campaign manager.
  • C. Mumbo
    "Mumbo" is a raw, bluesy rock track by Paul McCartney and Wings, known for its loose, jam-like feel and largely improvised vocals.
  • D. Munjani
    Munjani is an alternative name for the Munji language, an Eastern Iranian language spoken primarily in Afghanistan’s Munjan Valley.
  • E. Crystal the Monkey
    Crystal the Monkey is a capuchin monkey actress best known for her roles in films and TV shows such as "The Hangover Part II," "Night at the Museum," and "Community."
  • 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: Muno
Triple: [Florenville, hasSubdivision, Muno]
Generated description
Muno is a village in the municipality of Florenville in the Wallonia region of southern Belgium.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Muno
Target entity description: Muno is a village in the municipality of Florenville in the Wallonia region of southern Belgium.
  • A. Mook
    Mook is a village in the Dutch province of Limburg, known for its scenic location along the Maas River near the German border.
  • B. Mook
    Mook is a surname most notably associated with Robby Mook, an American political strategist and campaign manager.
  • C. Mumbo
    "Mumbo" is a raw, bluesy rock track by Paul McCartney and Wings, known for its loose, jam-like feel and largely improvised vocals.
  • D. Munjani
    Munjani is an alternative name for the Munji language, an Eastern Iranian language spoken primarily in Afghanistan’s Munjan Valley.
  • E. Crystal the Monkey
    Crystal the Monkey is a capuchin monkey actress best known for her roles in films and TV shows such as "The Hangover Part II," "Night at the Museum," and "Community."
  • 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_69d81c639e808190a0e4b4f3d31c6a59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2eb22e388190904fc87765176c91 completed April 14, 2026, 12:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbac9604cc819088cde0ad8271ad48 completed May 6, 2026, 9:03 p.m.
NEDg Description generation batch_69fbad35be6c8190aa329fa947cbdcd9 completed May 6, 2026, 9:05 p.m.
NED2 Entity disambiguation (via description) batch_69fbae42ef2c8190b653d95de94042bc completed May 6, 2026, 9:10 p.m.
Created at: April 9, 2026, 10:18 p.m.