Triple

T14057047
Position Surface form Disambiguated ID Type / Status
Subject Rejsekort E338245 entity
Predicate operator P179 FINISHED
Object Rejsekort A/S
Rejsekort A/S is the company responsible for managing Denmark’s nationwide electronic travel card system used across public transportation.
E1078998 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: Rejsekort A/S | Statement: [Rejsekort, operator, Rejsekort A/S]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rejsekort A/S
Context triple: [Rejsekort, operator, Rejsekort A/S]
  • A. Hurtigruten AS
    Hurtigruten AS is a Norwegian cruise and ferry company best known for operating passenger and cargo voyages along Norway’s coastal and expedition routes.
  • B. Scala A/S
    Scala A/S is a company known for developing specialized measurement and control instruments, including the Scala MM400.
  • C. Go-Ahead Nordic
    Go-Ahead Nordic is a Scandinavian rail operator that runs passenger train services in Norway, including routes serving major hubs like Oslo Central Station.
  • D. Metro Service A/S
    Metro Service A/S is the company responsible for operating and managing the Copenhagen Metro system in Denmark.
  • E. Copenhagen Airports A/S
    Copenhagen Airports A/S is the Danish company that owns and manages Copenhagen Airport and related airport operations in the Copenhagen area.
  • 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: Rejsekort A/S
Triple: [Rejsekort, operator, Rejsekort A/S]
Generated description
Rejsekort A/S is the company responsible for managing Denmark’s nationwide electronic travel card system used across public transportation.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Rejsekort A/S
Target entity description: Rejsekort A/S is the company responsible for managing Denmark’s nationwide electronic travel card system used across public transportation.
  • A. Hurtigruten AS
    Hurtigruten AS is a Norwegian cruise and ferry company best known for operating passenger and cargo voyages along Norway’s coastal and expedition routes.
  • B. Scala A/S
    Scala A/S is a company known for developing specialized measurement and control instruments, including the Scala MM400.
  • C. Go-Ahead Nordic
    Go-Ahead Nordic is a Scandinavian rail operator that runs passenger train services in Norway, including routes serving major hubs like Oslo Central Station.
  • D. Metro Service A/S
    Metro Service A/S is the company responsible for operating and managing the Copenhagen Metro system in Denmark.
  • E. Copenhagen Airports A/S
    Copenhagen Airports A/S is the Danish company that owns and manages Copenhagen Airport and related airport operations in the Copenhagen area.
  • 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_69d81c67ba6c819091935650dfb3b895 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de3c8e6d008190af8892f34c5cefbd completed April 14, 2026, 1:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcb6608cf8819087ed5d890b82650a completed May 7, 2026, 3:57 p.m.
NEDg Description generation batch_69fcc91405888190ba808b2051f57f19 completed May 7, 2026, 5:17 p.m.
NED2 Entity disambiguation (via description) batch_69fcc9be3f448190b2edd96c4159f923 completed May 7, 2026, 5:19 p.m.
Created at: April 9, 2026, 10:20 p.m.