Triple

T5807229
Position Surface form Disambiguated ID Type / Status
Subject Montgomery County Airpark E128775 entity
Predicate IATA code P2569 FINISHED
Object GAI
GAI is the IATA airport code for Montgomery County Airpark, a public general aviation airport serving the Gaithersburg, Maryland area in the United States.
 E548662 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: GAI | Statement: [Montgomery County Airpark, IATA code, GAI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: GAI
Context triple: [Montgomery County Airpark, IATA code, GAI]
  • A. xAI
    xAI is an artificial intelligence company focused on developing advanced AI systems, founded and led by entrepreneur Elon Musk.
  • B. GIO
    GIO is an Australian insurance company best known for providing a wide range of general insurance products, including car, home, and business insurance.
  • C. Grok
    Grok is an AI chatbot developed by xAI, designed to provide conversational access to real-time information and reasoning capabilities.
  • D. GIG
    GIG is the IATA airport code for Rio de Janeiro–Galeão International Airport, the main international gateway serving Rio de Janeiro, Brazil.
  • E. Gesaffelstein
    Gesaffelstein is a French electronic music producer and DJ known for his dark, industrial techno sound and collaborations with major artists like Kanye West.
  • 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: GAI
Triple: [Montgomery County Airpark, IATA code, GAI]
Generated description
GAI is the IATA airport code for Montgomery County Airpark, a public general aviation airport serving the Gaithersburg, Maryland area in the United States.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: GAI
Target entity description: GAI is the IATA airport code for Montgomery County Airpark, a public general aviation airport serving the Gaithersburg, Maryland area in the United States.
  • A. xAI
    xAI is an artificial intelligence company focused on developing advanced AI systems, founded and led by entrepreneur Elon Musk.
  • B. GIO
    GIO is an Australian insurance company best known for providing a wide range of general insurance products, including car, home, and business insurance.
  • C. Grok
    Grok is an AI chatbot developed by xAI, designed to provide conversational access to real-time information and reasoning capabilities.
  • D. GIG
    GIG is the IATA airport code for Rio de Janeiro–Galeão International Airport, the main international gateway serving Rio de Janeiro, Brazil.
  • E. Gesaffelstein
    Gesaffelstein is a French electronic music producer and DJ known for his dark, industrial techno sound and collaborations with major artists like Kanye West.
  • 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_69c00846a0d881909e46841f8e156b64 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02b17417081908779741b9bfbb720 completed March 22, 2026, 5:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0983a0b648190ba2c76434d3b1b58 completed March 23, 2026, 1:32 a.m.
NEDg Description generation batch_69c099c8c9448190a3847ac984123d7a completed March 23, 2026, 1:39 a.m.
NED2 Entity disambiguation (via description) batch_69c09a458c488190b9e2716fc47cf601 completed March 23, 2026, 1:41 a.m.
Created at: March 22, 2026, 3:52 p.m.