Triple

T17052732
Position Surface form Disambiguated ID Type / Status
Subject Kampen station E413740 entity
Predicate hasStationCode P1289 FINISHED
Object Kpn
Kpn is the official station code used to identify Kampen railway station in the Netherlands.
E1248490 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: Kpn | Statement: [Kampen station, hasStationCode, Kpn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kpn
Context triple: [Kampen station, hasStationCode, Kpn]
  • A. KPN
    KPN is the abbreviation commonly used for the Korean People's Navy, the maritime branch of North Korea's armed forces.
  • B. Telkom
    Telkom is a major South African telecommunications company that provides fixed-line, mobile, and data services across the country.
  • C. Telenet Group
    Telenet Group is a major Belgian telecommunications and entertainment provider offering services such as broadband internet, television, and mobile telephony.
  • D. Cablecom
    Cablecom was a major Swiss cable television and telecommunications provider that later became known as UPC Switzerland.
  • E. Sogetel
    Sogetel is a film and television production company known for producing European, particularly French-language, cinematic works.
  • 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: Kpn
Triple: [Kampen station, hasStationCode, Kpn]
Generated description
Kpn is the official station code used to identify Kampen railway station in the Netherlands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kpn
Target entity description: Kpn is the official station code used to identify Kampen railway station in the Netherlands.
  • A. KPN
    KPN is the abbreviation commonly used for the Korean People's Navy, the maritime branch of North Korea's armed forces.
  • B. Telkom
    Telkom is a major South African telecommunications company that provides fixed-line, mobile, and data services across the country.
  • C. Telenet Group
    Telenet Group is a major Belgian telecommunications and entertainment provider offering services such as broadband internet, television, and mobile telephony.
  • D. Cablecom
    Cablecom was a major Swiss cable television and telecommunications provider that later became known as UPC Switzerland.
  • E. Sogetel
    Sogetel is a film and television production company known for producing European, particularly French-language, cinematic works.
  • 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_69d886cde3d481908d4d01ba88ba7eb7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3daa3324881908d9e445ba1cfe109 completed April 18, 2026, 7:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012343eca0819086a07511c5d22878 completed May 11, 2026, 12:31 a.m.
NEDg Description generation batch_6a012585a1548190a112f55e2d84ccac completed May 11, 2026, 12:40 a.m.
NED2 Entity disambiguation (via description) batch_6a0126536c348190b9b2eadb4969f8c2 completed May 11, 2026, 12:44 a.m.
Created at: April 10, 2026, 5:34 a.m.