Triple

T1189830
Position Surface form Disambiguated ID Type / Status
Subject Miami International Airport E25331 entity
Predicate hasConcourses P1656 FINISHED
Object 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.
 E136218 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: J | Statement: [Miami International Airport, hasConcourses, J]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: J
Context triple: [Miami International Airport, hasConcourses, J]
  • A. 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.
  • B. JO
    JO is the two-letter ISO 3166-1 alpha-2 country code assigned to the Hashemite Kingdom of Jordan.
  • C. JB
    JB is the standard abbreviation for the Jerusalem Bible, a widely used English translation of the Catholic Bible first published in the 1960s.
  • D. Jo
    Jo is a given name used across various cultures, often as a short form of names like Joseph, Joanna, or Jonathan.
  • E. JR
    JR is a French street artist and photographer renowned for his large-scale public art installations that transform urban spaces and address social and political issues worldwide.
  • 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: J
Triple: [Miami International Airport, hasConcourses, J]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: J
Target entity description: 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.
  • A. 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.
  • B. JO
    JO is the two-letter ISO 3166-1 alpha-2 country code assigned to the Hashemite Kingdom of Jordan.
  • C. JB
    JB is the standard abbreviation for the Jerusalem Bible, a widely used English translation of the Catholic Bible first published in the 1960s.
  • D. Jo
    Jo is a given name used across various cultures, often as a short form of names like Joseph, Joanna, or Jonathan.
  • E. JR
    JR is a French street artist and photographer renowned for his large-scale public art installations that transform urban spaces and address social and political issues worldwide.
  • 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_69a49427d98881908646d6c63b8cea1e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd57c3c481908bdca483fcaa3297 completed March 1, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac764ccb1c8190a302137a0e67cb88 completed March 7, 2026, 7:02 p.m.
NEDg Description generation batch_69ac76e1b430819092669c6e83d7a62c completed March 7, 2026, 7:05 p.m.
NED2 Entity disambiguation (via description) batch_69ac77670fa08190827ef34ba9d52a70 completed March 7, 2026, 7:07 p.m.
Created at: March 1, 2026, 7:45 p.m.