Triple

T23496676
Position Surface form Disambiguated ID Type / Status
Subject Kannur railway station E571722 entity
Predicate hasStationCode P1289 FINISHED
Object CAN
CAN is the official Indian Railways station code for Kannur railway station in Kerala, India.
 E1588578 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: CAN | Statement: [Kannur railway station, hasStationCode, CAN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CAN
Context triple: [Kannur railway station, hasStationCode, CAN]
  • A. CAN
    CAN is a South American regional integration organization that promotes economic and social cooperation among its member countries, including Bolivia, Colombia, Ecuador, and Peru.
  • B. CAN
    CAN is the standard international abbreviation for the Canada men's national ice hockey team, one of the most successful and historically dominant teams in world ice hockey.
  • C. CAN
    CAN is the FIFA country code for Canada, the North American nation whose teams and players participate in international soccer competitions.
  • D. CAN
    CAN is the three-letter IATA airport code for Guangzhou Baiyun International Airport, a major air transport hub in southern China.
  • E. CAN
    CAN is the three-letter National Olympic Committee code representing Canada in international Olympic competitions, including the Olympic Winter Games.
  • 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: CAN
Triple: [Kannur railway station, hasStationCode, CAN]
Generated description
CAN is the official Indian Railways station code for Kannur railway station in Kerala, India.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CAN
Target entity description: CAN is the official Indian Railways station code for Kannur railway station in Kerala, India.
  • A. CAN
    CAN is the three-letter IATA airport code for Guangzhou Baiyun International Airport, a major air transport hub in southern China.
  • B. CAN
    CAN is the FIFA country code for Canada, the North American nation whose teams and players participate in international soccer competitions.
  • C. CAN
    CAN is the three-letter National Olympic Committee code representing Canada in international Olympic competitions, including the Olympic Winter Games.
  • D. CAN
    CAN is a prominent umbrella organization representing and coordinating various Christian denominations and churches across Nigeria.
  • E. CAN
    CAN is the standard international abbreviation for the Canada men's national ice hockey team, one of the most successful and historically dominant teams in world ice hockey.
  • 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_69e245b4829881909b77a70e942bbd54 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a7e00384819092729319a378d4ab completed April 29, 2026, 6:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c8271bd388190acc97e26e5c142f8 completed May 19, 2026, 3:32 p.m.
NEDg Description generation batch_6a0ca6f229308190bf72b52fd44144d3 completed May 19, 2026, 6:07 p.m.
NED2 Entity disambiguation (via description) batch_6a0ca7e9e9988190ac3bedb9ecb8ce06 completed May 19, 2026, 6:11 p.m.
Created at: April 17, 2026, 6:05 p.m.