Triple

T10083531
Position Surface form Disambiguated ID Type / Status
Subject Renton Municipal Airport E213962 entity
Predicate IATAcode P418 FINISHED
Object RNT
RNT is the IATA airport code for Renton Municipal Airport, a public airport serving the city of Renton in Washington State, USA.
 E841435 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: RNT | Statement: [Renton Municipal Airport, IATAcode, RNT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: RNT
Context triple: [Renton Municipal Airport, IATAcode, RNT]
  • A. NRT
    NRT is the three-letter IATA airport code for Narita International Airport, a major international gateway serving the Tokyo metropolitan area in Japan.
  • B. RTN
    RTN is the former stock ticker symbol for Raytheon Company, a major U.S. defense and aerospace contractor.
  • C. RNR
    RNR is the abbreviation for the Royal Naval Reserve, the volunteer reserve force of the United Kingdom’s Royal Navy.
  • D. REN
    REN is a blockchain-based project and protocol focused on enabling cross-chain liquidity and interoperability between different cryptocurrency networks.
  • E. RUT
    RUT is the ticker symbol for the Russell 2000 Index, a major U.S. stock market index tracking the performance of approximately 2,000 small-cap companies.
  • 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: RNT
Triple: [Renton Municipal Airport, IATAcode, RNT]
Generated description
RNT is the IATA airport code for Renton Municipal Airport, a public airport serving the city of Renton in Washington State, USA.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: RNT
Target entity description: RNT is the IATA airport code for Renton Municipal Airport, a public airport serving the city of Renton in Washington State, USA.
  • A. NRT
    NRT is the three-letter IATA airport code for Narita International Airport, a major international gateway serving the Tokyo metropolitan area in Japan.
  • B. RTN
    RTN is the former stock ticker symbol for Raytheon Company, a major U.S. defense and aerospace contractor.
  • C. RNR
    RNR is the abbreviation for the Royal Naval Reserve, the volunteer reserve force of the United Kingdom’s Royal Navy.
  • D. REN
    REN is a blockchain-based project and protocol focused on enabling cross-chain liquidity and interoperability between different cryptocurrency networks.
  • E. RUT
    RUT is the ticker symbol for the Russell 2000 Index, a major U.S. stock market index tracking the performance of approximately 2,000 small-cap companies.
  • 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_69ca839bf730819086900c323c9b8c95 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd04352d081908f676444cd2d2578 completed April 2, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b675f4b08190bd8285f210191b93 completed April 5, 2026, 7:22 p.m.
NEDg Description generation batch_69d2ba645ec08190b33388a40ca7582e completed April 5, 2026, 7:39 p.m.
NED2 Entity disambiguation (via description) batch_69d2babd01908190b5c9f9c3541361ee completed April 5, 2026, 7:40 p.m.
Created at: March 30, 2026, 9 p.m.