Triple

T2400202
Position Surface form Disambiguated ID Type / Status
Subject Arrondissement of Verviers E47747 entity
Predicate contains P35 FINISHED
Object Lierneux
Lierneux is a rural municipality in the province of Liège in Wallonia, Belgium, known for its forests, valleys, and quiet countryside.
E262733 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: Lierneux | Statement: [Arrondissement of Verviers, contains, Lierneux]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lierneux
Context triple: [Arrondissement of Verviers, contains, Lierneux]
  • A. Lebrun
    Lebrun is a French surname borne by various notable figures in politics, arts, and other fields.
  • B. Roussel
    Roussel is a surname of French origin, often used as an alternative spelling of Russell.
  • C. Ganthier
    Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
  • D. Tournier
    Tournier is a surname of French origin, sometimes used as a variant of the English surname Turner.
  • E. Brévands
    Brévands is a former commune in the Manche department of northwestern France, now part of the larger municipality of Carentan-les-Marais.
  • 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: Lierneux
Triple: [Arrondissement of Verviers, contains, Lierneux]
Generated description
Lierneux is a rural municipality in the province of Liège in Wallonia, Belgium, known for its forests, valleys, and quiet countryside.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lierneux
Target entity description: Lierneux is a rural municipality in the province of Liège in Wallonia, Belgium, known for its forests, valleys, and quiet countryside.
  • A. Lebrun
    Lebrun is a French surname borne by various notable figures in politics, arts, and other fields.
  • B. Roussel
    Roussel is a surname of French origin, often used as an alternative spelling of Russell.
  • C. Ganthier
    Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
  • D. Tournier
    Tournier is a surname of French origin, sometimes used as a variant of the English surname Turner.
  • E. Brévands
    Brévands is a former commune in the Manche department of northwestern France, now part of the larger municipality of Carentan-les-Marais.
  • 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_69a88a1c450c81909f61abb8b6863885 completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abc8c95d8c819088e4bb4fb32452ae completed March 7, 2026, 6:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69aeb3e319c481908537fe278f6f0a67 completed March 9, 2026, 11:49 a.m.
NEDg Description generation batch_69aeb4b942b08190addc2885fbda0e41 completed March 9, 2026, 11:53 a.m.
NED2 Entity disambiguation (via description) batch_69aeb557247c8190920ce3a5db388800 completed March 9, 2026, 11:56 a.m.
Created at: March 4, 2026, 7:57 p.m.