Triple

T2966809
Position Surface form Disambiguated ID Type / Status
Subject South Kensington tube station E80185 entity
Predicate stationCode P1289 FINISHED
Object SKN
SKN is the station code for South Kensington tube station, a major London Underground interchange serving the South Kensington area.
 E314787 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: SKN | Statement: [South Kensington tube station, stationCode, SKN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SKN
Context triple: [South Kensington tube station, stationCode, SKN]
  • A. SKC
    SKC is the commonly used abbreviation for Sporting Kansas City, a professional Major League Soccer club based in Kansas City.
  • B. SK
    SK is the vehicle registration code used on license plates for vehicles registered in Skopje, the capital city of North Macedonia.
  • C. SK
    SK is the postcode area covering Stockport and surrounding parts of Greater Manchester and nearby counties in North West England.
  • D. SK
    SK is the IATA airline designator used worldwide to identify Scandinavian Airlines on tickets, timetables, and flight information systems.
  • E. Sk
    Sk is the currency symbol that was used to denote the Slovak koruna, the former national currency of Slovakia before adoption of the euro.
  • 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: SKN
Triple: [South Kensington tube station, stationCode, SKN]
Generated description
SKN is the station code for South Kensington tube station, a major London Underground interchange serving the South Kensington area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SKN
Target entity description: SKN is the station code for South Kensington tube station, a major London Underground interchange serving the South Kensington area.
  • A. SKC
    SKC is the commonly used abbreviation for Sporting Kansas City, a professional Major League Soccer club based in Kansas City.
  • B. SK
    SK is the vehicle registration code used on license plates for vehicles registered in Skopje, the capital city of North Macedonia.
  • C. SK
    SK is the postcode area covering Stockport and surrounding parts of Greater Manchester and nearby counties in North West England.
  • D. SK
    SK is the IATA airline designator used worldwide to identify Scandinavian Airlines on tickets, timetables, and flight information systems.
  • E. Sk
    Sk is the currency symbol that was used to denote the Slovak koruna, the former national currency of Slovakia before adoption of the euro.
  • 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_69ad8b1341848190bd19dbf46892887d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad996e93788190ba9883714d4dfa0c completed March 8, 2026, 3:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0fc9fcfa48190a5e23ec1f3f01038 completed March 11, 2026, 5:24 a.m.
NEDg Description generation batch_69b100c1bfd48190ab71f460afb096e3 completed March 11, 2026, 5:42 a.m.
NED2 Entity disambiguation (via description) batch_69b10126bd788190b40f3ce1a8a547aa completed March 11, 2026, 5:44 a.m.
Created at: March 8, 2026, 2:58 p.m.