Triple

T9598118
Position Surface form Disambiguated ID Type / Status
Subject Square Victoria–OACI station E231782 entity
Predicate hasCode P9567 FINISHED
Object SVO
SVO is the station code used to identify Square Victoria–OACI, a Montreal Metro station on the Orange Line.
 E808918 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: SVO | Statement: [Square Victoria–OACI station, hasCode, SVO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SVO
Context triple: [Square Victoria–OACI station, hasCode, SVO]
  • A. SVO
    SVO is the three-letter IATA airport code for Sheremetyevo International Airport, one of Moscow’s major international air hubs in Russia.
  • B. SOV
    SOV is the National Rail station code for Southend Victoria railway station in Southend-on-Sea, Essex, England.
  • C. FSVO
    FSVO is the Swiss federal authority responsible for overseeing food safety, animal health, and animal welfare in Switzerland.
  • D. SOU
    SOU is the three-letter IATA airport code for Southampton Airport in Hampshire, England.
  • E. SOU
    SOU is the three-letter National Rail station code for Southampton Central railway station in Hampshire, England.
  • 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: SVO
Triple: [Square Victoria–OACI station, hasCode, SVO]
Generated description
SVO is the station code used to identify Square Victoria–OACI, a Montreal Metro station on the Orange Line.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SVO
Target entity description: SVO is the station code used to identify Square Victoria–OACI, a Montreal Metro station on the Orange Line.
  • A. SVO
    SVO is the three-letter IATA airport code for Sheremetyevo International Airport, one of Moscow’s major international air hubs in Russia.
  • B. SOV
    SOV is the National Rail station code for Southend Victoria railway station in Southend-on-Sea, Essex, England.
  • C. FSVO
    FSVO is the Swiss federal authority responsible for overseeing food safety, animal health, and animal welfare in Switzerland.
  • D. SOU
    SOU is the three-letter IATA airport code for Southampton Airport in Hampshire, England.
  • E. SOU
    SOU is the three-letter National Rail station code for Southampton Central railway station in Hampshire, England.
  • 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_69ca8484838c8190b2049199d22fef70 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9a366d3481908db62e476958eafe completed April 1, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1619f4170819092ae90b2896b0855 completed April 4, 2026, 7:08 p.m.
NEDg Description generation batch_69d163c1abfc8190baae07681ea13104 completed April 4, 2026, 7:17 p.m.
NED2 Entity disambiguation (via description) batch_69d16476b9188190ab28efb0433c99b0 completed April 4, 2026, 7:20 p.m.
Created at: March 30, 2026, 8:07 p.m.