Triple

T2285985
Position Surface form Disambiguated ID Type / Status
Subject Waterloo Regional Airport E51392 entity
Predicate IATAcode P418 FINISHED
Object ALO
ALO is the three-letter IATA airport code for Waterloo Regional Airport in Waterloo, Iowa, United States.
 E252376 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: ALO | Statement: [Waterloo Regional Airport, IATAcode, ALO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ALO
Context triple: [Waterloo Regional Airport, IATAcode, ALO]
  • A. ALO
    ALO is the Arab Labor Organization, a specialized Arab League body that promotes labor standards, employment policies, and workers’ rights across Arab countries.
  • B. Al
    Al is a common shortened form of given names such as Albert, Alan, or Alexander.
  • C. AL
    AL is the common abbreviation for the American League, one of the two major professional baseball leagues that make up Major League Baseball in the United States and Canada.
  • D. AL
    AL is the official postal abbreviation for the Brazilian state of Alagoas, located in the country's Northeast region.
  • E. Ale
    Ale is a common short form of the Italian given name Alessandro, often used as a casual or affectionate nickname.
  • 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: ALO
Triple: [Waterloo Regional Airport, IATAcode, ALO]
Generated description
ALO is the three-letter IATA airport code for Waterloo Regional Airport in Waterloo, Iowa, United States.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ALO
Target entity description: ALO is the three-letter IATA airport code for Waterloo Regional Airport in Waterloo, Iowa, United States.
  • A. ALO
    ALO is the Arab Labor Organization, a specialized Arab League body that promotes labor standards, employment policies, and workers’ rights across Arab countries.
  • B. Al
    Al is a common shortened form of given names such as Albert, Alan, or Alexander.
  • C. AL
    AL is the common abbreviation for the American League, one of the two major professional baseball leagues that make up Major League Baseball in the United States and Canada.
  • D. AL
    AL is the official postal abbreviation for the Brazilian state of Alagoas, located in the country's Northeast region.
  • E. Ale
    Ale is a common short form of the Italian given name Alessandro, often used as a casual or affectionate nickname.
  • 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_69a88b08e4308190bdac9aebcca1c91a completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc24730208190af8a5cf443d334f7 completed March 7, 2026, 6:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae7f1759b081908842f7ad189994ff completed March 9, 2026, 8:04 a.m.
NEDg Description generation batch_69ae7fc194488190bb71124f0225a521 completed March 9, 2026, 8:07 a.m.
NED2 Entity disambiguation (via description) batch_69ae802d03648190a71303daf20e6162 completed March 9, 2026, 8:09 a.m.
Created at: March 4, 2026, 7:48 p.m.