Triple

T13946567
Position Surface form Disambiguated ID Type / Status
Subject Almería Airport E335399 entity
Predicate IATAcode P418 FINISHED
Object LEI
LEI is the three-letter IATA airport code for Almería Airport in Spain.
E1070543 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: LEI | Statement: [Almería Airport, IATAcode, LEI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LEI
Context triple: [Almería Airport, IATAcode, LEI]
  • A. LEI
    LEI is the commonly used abbreviation for Leiden University, one of the oldest and most prestigious universities in the Netherlands.
  • B. LIEA
    LIEA is the ICAO airport code for Alghero-Fertilia Airport, a commercial airport serving the city of Alghero on the Italian island of Sardinia.
  • C. LEU
    LEU is the National Rail station code for Leuchars (for St Andrews) railway station in Fife, Scotland.
  • D. LEAL
    LEAL is the ICAO airport code for Alicante–Elche Airport, the main international airport serving Spain’s Costa Blanca region.
  • E. lei
    The leu (plural: lei) is the official currency of Romania, used for everyday transactions and financial operations throughout the country.
  • 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: LEI
Triple: [Almería Airport, IATAcode, LEI]
Generated description
LEI is the three-letter IATA airport code for Almería Airport in Spain.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: LEI
Target entity description: LEI is the three-letter IATA airport code for Almería Airport in Spain.
  • A. LEI
    LEI is the commonly used abbreviation for Leiden University, one of the oldest and most prestigious universities in the Netherlands.
  • B. LIEA
    LIEA is the ICAO airport code for Alghero-Fertilia Airport, a commercial airport serving the city of Alghero on the Italian island of Sardinia.
  • C. LEU
    LEU is the National Rail station code for Leuchars (for St Andrews) railway station in Fife, Scotland.
  • D. LEAL
    LEAL is the ICAO airport code for Alicante–Elche Airport, the main international airport serving Spain’s Costa Blanca region.
  • E. lei
    The leu (plural: lei) is the official currency of Romania, used for everyday transactions and financial operations throughout the country.
  • 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_69d81c6081b88190b53e317c3370c8fe completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e10f60c81908ee9636e85c070ff completed April 14, 2026, 12:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7ce903c5c8190b72d83a5b842ad70 completed May 3, 2026, 10:39 p.m.
NEDg Description generation batch_69f9fd5d4abc8190aa10d9f1c9f7f9c9 completed May 5, 2026, 2:23 p.m.
NED2 Entity disambiguation (via description) batch_69fb14bfa2c081908381bb74f040c6c8 completed May 6, 2026, 10:15 a.m.
Created at: April 9, 2026, 10:17 p.m.