Triple

T9174737
Position Surface form Disambiguated ID Type / Status
Subject BB 15000 E220167 entity
Predicate usedOnLine P15252 FINISHED
Object Paris–Luxembourg
Paris–Luxembourg is a major international railway route linking the French capital Paris with the Grand Duchy of Luxembourg.
 E782999 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: Paris–Luxembourg | Statement: [BB 15000, usedOnLine, Paris–Luxembourg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Paris–Luxembourg
Context triple: [BB 15000, usedOnLine, Paris–Luxembourg]
  • A. Paris–Brussels
    Paris–Brussels is a major international high-speed rail corridor linking the capitals of France and Belgium.
  • B. Paris–Strasbourg
    Paris–Strasbourg is a major high-speed rail corridor in France linking the capital with the Alsatian city near the German border.
  • C. Frankfurt–Paris
    Frankfurt–Paris is a major international high-speed rail connection linking Germany and France, commonly served by InterCityExpress (ICE) trains.
  • D. Brussels–Cologne
    Brussels–Cologne is a major international high-speed rail corridor linking Belgium’s capital with the German city of Cologne.
  • E. Frankfurt–Brussels
    Frankfurt–Brussels is a major international high-speed rail route linking Germany and Belgium, commonly served by InterCityExpress (ICE) trains.
  • 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: Paris–Luxembourg
Triple: [BB 15000, usedOnLine, Paris–Luxembourg]
Generated description
Paris–Luxembourg is a major international railway route linking the French capital Paris with the Grand Duchy of Luxembourg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Paris–Luxembourg
Target entity description: Paris–Luxembourg is a major international railway route linking the French capital Paris with the Grand Duchy of Luxembourg.
  • A. Paris–Brussels
    Paris–Brussels is a major international high-speed rail corridor linking the capitals of France and Belgium.
  • B. Paris–Strasbourg
    Paris–Strasbourg is a major high-speed rail corridor in France linking the capital with the Alsatian city near the German border.
  • C. Frankfurt–Paris
    Frankfurt–Paris is a major international high-speed rail connection linking Germany and France, commonly served by InterCityExpress (ICE) trains.
  • D. Brussels–Cologne
    Brussels–Cologne is a major international high-speed rail corridor linking Belgium’s capital with the German city of Cologne.
  • E. Frankfurt–Brussels
    Frankfurt–Brussels is a major international high-speed rail route linking Germany and Belgium, commonly served by InterCityExpress (ICE) trains.
  • 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_69ca83e467108190abcae6a33b3d4dad completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccbfa2f9708190a955bf28a4f04004 completed April 1, 2026, 6:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69d05c0a91ec8190a97002660b66aabe completed April 4, 2026, 12:32 a.m.
NEDg Description generation batch_69d05ca2a3f881909ed9193560b5b0cd completed April 4, 2026, 12:34 a.m.
NED2 Entity disambiguation (via description) batch_69d05d4191f8819083c0ae2a68059c93 completed April 4, 2026, 12:37 a.m.
Created at: March 30, 2026, 7:23 p.m.