Triple

T10181543
Position Surface form Disambiguated ID Type / Status
Subject Hawthorne Municipal Airport E236796 entity
Predicate IATAcode P418 FINISHED
Object HHR
HHR is the IATA airport code for Hawthorne Municipal Airport, a public airport serving the city of Hawthorne in Los Angeles County, California.
 E845747 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: HHR | Statement: [Hawthorne Municipal Airport, IATAcode, HHR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: HHR
Context triple: [Hawthorne Municipal Airport, IATAcode, HHR]
  • A. H4H
    H4H is a U.S. federal mortgage relief initiative designed to help struggling homeowners refinance into more affordable, government-insured loans.
  • B. HARV
    HARV is the standard abbreviation used for the Harvard Crimson men's basketball team in collegiate athletics contexts.
  • C. HOR
    HOR is the IATA airport code for Horta Airport, which serves the island of Faial in Portugal’s Azores archipelago.
  • D. HOR
    HOR is the National Rail station code for Horley railway station in Surrey, England.
  • E. HRL
    HRL is a renowned research center known for pioneering work in fields such as microelectronics, information and quantum sciences, and advanced materials.
  • 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: HHR
Triple: [Hawthorne Municipal Airport, IATAcode, HHR]
Generated description
HHR is the IATA airport code for Hawthorne Municipal Airport, a public airport serving the city of Hawthorne in Los Angeles County, California.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: HHR
Target entity description: HHR is the IATA airport code for Hawthorne Municipal Airport, a public airport serving the city of Hawthorne in Los Angeles County, California.
  • A. H4H
    H4H is a U.S. federal mortgage relief initiative designed to help struggling homeowners refinance into more affordable, government-insured loans.
  • B. HARV
    HARV is the standard abbreviation used for the Harvard Crimson men's basketball team in collegiate athletics contexts.
  • C. HOR
    HOR is the IATA airport code for Horta Airport, which serves the island of Faial in Portugal’s Azores archipelago.
  • D. HOR
    HOR is the National Rail station code for Horley railway station in Surrey, England.
  • E. HRL
    HRL is a renowned research center known for pioneering work in fields such as microelectronics, information and quantum sciences, and advanced materials.
  • 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_69ca84d7260c8190bfbec36762943f37 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cded32b91c8190b01ad37b2456080a completed April 2, 2026, 4:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69d3013f0c54819092ee9c2c46fdf69e completed April 6, 2026, 12:41 a.m.
NEDg Description generation batch_69d3028a4384819094a7daef7287e54f completed April 6, 2026, 12:47 a.m.
NED2 Entity disambiguation (via description) batch_69d302e9d2688190bc292f8f2287c458 completed April 6, 2026, 12:48 a.m.
Created at: March 30, 2026, 9:12 p.m.