Triple

T17225444
Position Surface form Disambiguated ID Type / Status
Subject Jean-Drapeau station E418101 entity
Predicate code P1537 FINISHED
Object JE
JE is the station code used to identify Jean-Drapeau station in the Montreal Metro system.
 E1257538 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: JE | Statement: [Jean-Drapeau station, code, JE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: JE
Context triple: [Jean-Drapeau station, code, JE]
  • A. JI
    JI is the IATA airline designator assigned to Meraj Airlines, an Iranian passenger carrier.
  • B. JO
    JO is the two-letter ISO 3166-1 alpha-2 country code assigned to the Hashemite Kingdom of Jordan.
  • C. J
    J is a New York City Subway service that runs through Brooklyn and Queens into Manhattan, serving neighborhoods in eastern Brooklyn and southern Queens.
  • D. J
    J is the streetwise, impulsive teenage grandson in the TV series "Animal Kingdom," who becomes entangled in his criminal family's operations.
  • E. J
    J is one of the passenger concourses at Miami International Airport, serving as a terminal area with gates, amenities, and airline operations for departing and arriving flights.
  • 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: JE
Triple: [Jean-Drapeau station, code, JE]
Generated description
JE is the station code used to identify Jean-Drapeau station in the Montreal Metro system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: JE
Target entity description: JE is the station code used to identify Jean-Drapeau station in the Montreal Metro system.
  • A. JI
    JI is the IATA airline designator assigned to Meraj Airlines, an Iranian passenger carrier.
  • B. JO
    JO is the two-letter ISO 3166-1 alpha-2 country code assigned to the Hashemite Kingdom of Jordan.
  • C. J
    J is a New York City Subway service that runs through Brooklyn and Queens into Manhattan, serving neighborhoods in eastern Brooklyn and southern Queens.
  • D. J
    J is one of the passenger concourses at Miami International Airport, serving as a terminal area with gates, amenities, and airline operations for departing and arriving flights.
  • E. J
    J is the streetwise, impulsive teenage grandson in the TV series "Animal Kingdom," who becomes entangled in his criminal family's operations.
  • 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_69d886d779488190b131369541c04e7d completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42de0a8dc819093d9c8fb4f80342c completed April 19, 2026, 1:20 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01675cc70881909cf39b2e229f5d1e completed May 11, 2026, 5:21 a.m.
NEDg Description generation batch_6a016a5f58408190b42a8da742aa2f5b completed May 11, 2026, 5:34 a.m.
NED2 Entity disambiguation (via description) batch_6a016b0e72588190b1ba2b45f0425d3d completed May 11, 2026, 5:37 a.m.
Created at: April 10, 2026, 5:38 a.m.