Triple

T13239779
Position Surface form Disambiguated ID Type / Status
Subject Girona–Costa Brava Airport E315249 entity
Predicate ICAOcode P419 FINISHED
Object LEGE
LEGE is the ICAO airport code for Girona–Costa Brava Airport, an international airport serving the Girona region in Catalonia, Spain.
 E1028506 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: LEGE | Statement: [Girona–Costa Brava Airport, ICAOcode, LEGE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LEGE
Context triple: [Girona–Costa Brava Airport, ICAOcode, LEGE]
  • A. LEG
    LEG is the National Rail station code for Lea Green railway station in Merseyside, England.
  • B. LEG
    LEG is the International Maritime Organization’s Legal Committee, responsible for developing and maintaining international maritime law and liability conventions.
  • C. LEG
    LEG is the commonly used abbreviation for the Faculty of Law, Economics and Governance at Utrecht University, which combines legal, economic and governance disciplines.
  • D. LETGS
    LETGS is a high-resolution X-ray grating spectrometer aboard NASA’s Chandra X-ray Observatory used to disperse and analyze X-ray emissions from cosmic sources.
  • E. LEMG
    LEMG is the ICAO airport code for Málaga–Costa del Sol Airport, the main international airport serving Málaga and Spain’s Costa del Sol region.
  • 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: LEGE
Triple: [Girona–Costa Brava Airport, ICAOcode, LEGE]
Generated description
LEGE is the ICAO airport code for Girona–Costa Brava Airport, an international airport serving the Girona region in Catalonia, Spain.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LEGE
Target entity description: LEGE is the ICAO airport code for Girona–Costa Brava Airport, an international airport serving the Girona region in Catalonia, Spain.
  • A. LEG
    LEG is the commonly used abbreviation for the Faculty of Law, Economics and Governance at Utrecht University, which combines legal, economic and governance disciplines.
  • B. LEG
    LEG is the National Rail station code for Lea Green railway station in Merseyside, England.
  • C. LEG
    LEG is the International Maritime Organization’s Legal Committee, responsible for developing and maintaining international maritime law and liability conventions.
  • D. LETGS
    LETGS is a high-resolution X-ray grating spectrometer aboard NASA’s Chandra X-ray Observatory used to disperse and analyze X-ray emissions from cosmic sources.
  • E. LEMG
    LEMG is the ICAO airport code for Málaga–Costa del Sol Airport, the main international airport serving Málaga and Spain’s Costa del Sol region.
  • 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_69d806b1072881909e46bd212259c5f0 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98d5850ac8190849a51da39efe5be completed April 10, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff323a3c8190b46b24e69e653105 completed May 3, 2026, 7:54 a.m.
NEDg Description generation batch_69f7013b3428819083c2bb6032aa08d4 completed May 3, 2026, 8:03 a.m.
NED2 Entity disambiguation (via description) batch_69f702b40f088190bc3c24321309dfb1 completed May 3, 2026, 8:09 a.m.
Created at: April 9, 2026, 9:23 p.m.