Triple

T5616400
Position Surface form Disambiguated ID Type / Status
Subject Lakeland Linder International Airport E147487 entity
Predicate IATAcode P418 FINISHED
Object LAL
LAL is the IATA airport code for Lakeland Linder International Airport, a public airport serving Lakeland, Florida.
 E537097 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: LAL | Statement: [Lakeland Linder International Airport, IATAcode, LAL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LAL
Context triple: [Lakeland Linder International Airport, IATAcode, LAL]
  • A. LAL
    LAL is the standard NBA abbreviation for the Los Angeles Lakers basketball franchise.
  • B. LAA
    LAA is the standard Major League Baseball abbreviation for the Los Angeles Angels franchise.
  • C. Lala
    Lala is an Indian honorific title traditionally used as a respectful prefix for educated or distinguished men, particularly in North India.
  • D. LAC
    LAC refers to the Los Angeles Clippers, a professional NBA basketball team based in Los Angeles and a crosstown rival of the Los Angeles Lakers.
  • E. LAF
    The Lebanese Armed Forces (LAF) are the military institution of Lebanon, responsible for defending the country’s sovereignty, maintaining internal security, and operating under a delicate sectarian balance.
  • 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: LAL
Triple: [Lakeland Linder International Airport, IATAcode, LAL]
Generated description
LAL is the IATA airport code for Lakeland Linder International Airport, a public airport serving Lakeland, Florida.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LAL
Target entity description: LAL is the IATA airport code for Lakeland Linder International Airport, a public airport serving Lakeland, Florida.
  • A. LAL
    LAL is the standard NBA abbreviation for the Los Angeles Lakers basketball franchise.
  • B. LAA
    LAA is the standard Major League Baseball abbreviation for the Los Angeles Angels franchise.
  • C. Lala
    Lala is an Indian honorific title traditionally used as a respectful prefix for educated or distinguished men, particularly in North India.
  • D. LAC
    LAC refers to the Los Angeles Clippers, a professional NBA basketball team based in Los Angeles and a crosstown rival of the Los Angeles Lakers.
  • E. LAF
    The Lebanese Armed Forces (LAF) are the military institution of Lebanon, responsible for defending the country’s sovereignty, maintaining internal security, and operating under a delicate sectarian balance.
  • 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_69c00905d4588190bd967842bbcf2219 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c021da7f848190bb1cd0270ad6398f completed March 22, 2026, 5:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d55b95c8190a5f3e2c05249c136 completed March 22, 2026, 8:13 p.m.
NEDg Description generation batch_69c04ed9159481909adeb9228ce59d0e completed March 22, 2026, 8:19 p.m.
NED2 Entity disambiguation (via description) batch_69c04f7b889c81909db7cb4baf40ed80 completed March 22, 2026, 8:22 p.m.
Created at: March 22, 2026, 3:39 p.m.