Triple

T5262102
Position Surface form Disambiguated ID Type / Status
Subject La Louvière E118848 entity
Predicate railConnection P848 FINISHED
Object Line to Brussels
Line to Brussels is a railway route connecting the city of La Louvière with Belgium’s capital, Brussels.
 E506573 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: Line to Brussels | Statement: [La Louvière, railConnection, Line to Brussels]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line to Brussels
Context triple: [La Louvière, railConnection, Line to Brussels]
  • A. Paris–Brussels
    Paris–Brussels is a major international high-speed rail corridor linking the capitals of France and Belgium.
  • B. Brussels–Cologne
    Brussels–Cologne is a major international high-speed rail corridor linking Belgium’s capital with the German city of Cologne.
  • C. London–Brussels
    London–Brussels is a major international high-speed rail route linking the United Kingdom and Belgium via the Channel Tunnel.
  • D. Paris–Amsterdam
    Paris–Amsterdam is a major international high-speed rail route linking the capitals of France and the Netherlands.
  • E. Paris–Vienna
    Paris–Vienna is the classic international rail corridor linking the French and Austrian capitals, historically served by luxury trains such as the Orient Express.
  • 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: Line to Brussels
Triple: [La Louvière, railConnection, Line to Brussels]
Generated description
Line to Brussels is a railway route connecting the city of La Louvière with Belgium’s capital, Brussels.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line to Brussels
Target entity description: Line to Brussels is a railway route connecting the city of La Louvière with Belgium’s capital, Brussels.
  • A. Paris–Brussels
    Paris–Brussels is a major international high-speed rail corridor linking the capitals of France and Belgium.
  • B. Brussels–Cologne
    Brussels–Cologne is a major international high-speed rail corridor linking Belgium’s capital with the German city of Cologne.
  • C. London–Brussels
    London–Brussels is a major international high-speed rail route linking the United Kingdom and Belgium via the Channel Tunnel.
  • D. Paris–Amsterdam
    Paris–Amsterdam is a major international high-speed rail route linking the capitals of France and the Netherlands.
  • E. Paris–Vienna
    Paris–Vienna is the classic international rail corridor linking the French and Austrian capitals, historically served by luxury trains such as the Orient Express.
  • 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_69bd446a42c88190b7ecbef006561d55 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7bd0c5f48190a1be89314c59f96b completed March 20, 2026, 4:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69befe85a3f88190ae014b18b1df202e completed March 21, 2026, 8:24 p.m.
NEDg Description generation batch_69beff56b42881909ff4f574ef87b693 completed March 21, 2026, 8:28 p.m.
NED2 Entity disambiguation (via description) batch_69bf00120fe88190817badb72977566e completed March 21, 2026, 8:31 p.m.
Created at: March 20, 2026, 1:50 p.m.