Triple

T10616249
Position Surface form Disambiguated ID Type / Status
Subject Governor Francisco Gabrielli International Airport E276127 entity
Predicate hasICAOcode P419 FINISHED
Object SAME
SAME is the ICAO airport code for Governor Francisco Gabrielli International Airport, the main airport serving Mendoza, Argentina.
 E874943 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: SAME | Statement: [Governor Francisco Gabrielli International Airport, hasICAOcode, SAME]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SAME
Context triple: [Governor Francisco Gabrielli International Airport, hasICAOcode, SAME]
  • A. Same
    Same is a town in northeastern Tanzania that serves as an administrative and commercial center near the Pare Mountains in the Kilimanjaro area.
  • B. SameYou
    SameYou is a charity focused on improving recovery and rehabilitation services for people who have experienced brain injury or stroke.
  • C. SAM
    SAM is the official FIFA trigramme used to represent the Samoa national under-20 football team in international competitions and records.
  • D. SAM
    SAM is the commonly used abbreviation for the South Australian Museum, a major natural history and cultural institution located in Adelaide, Australia.
  • E. SAM
    SAM is an online training and assessment platform used primarily in education for teaching and evaluating computer and digital literacy skills.
  • 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: SAME
Triple: [Governor Francisco Gabrielli International Airport, hasICAOcode, SAME]
Generated description
SAME is the ICAO airport code for Governor Francisco Gabrielli International Airport, the main airport serving Mendoza, Argentina.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SAME
Target entity description: SAME is the ICAO airport code for Governor Francisco Gabrielli International Airport, the main airport serving Mendoza, Argentina.
  • A. Same
    Same is a town in northeastern Tanzania that serves as an administrative and commercial center near the Pare Mountains in the Kilimanjaro area.
  • B. SameYou
    SameYou is a charity focused on improving recovery and rehabilitation services for people who have experienced brain injury or stroke.
  • C. SAM
    SAM is the commonly used abbreviation for the South Australian Museum, a major natural history and cultural institution located in Adelaide, Australia.
  • D. SAM
    SAM is the official FIFA trigramme used to represent the Samoa national under-20 football team in international competitions and records.
  • E. SAM
    SAM is an online training and assessment platform used primarily in education for teaching and evaluating computer and digital literacy skills.
  • 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_69d6aaf948d88190806cc3a8c47a3fb2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d6df6d76dc8190bd8d481fed3225d9 completed April 8, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69d95ecfb9bc81908d8ed054a30be441 completed April 10, 2026, 8:34 p.m.
NEDg Description generation batch_69d960f9b18881909c56f8f3a8499860 completed April 10, 2026, 8:43 p.m.
NED2 Entity disambiguation (via description) batch_69d9615b821481909e2061739641b114 completed April 10, 2026, 8:45 p.m.
Created at: April 8, 2026, 7:33 p.m.