Triple

T2210710
Position Surface form Disambiguated ID Type / Status
Subject Augusta State Airport E50910 entity
Predicate ICAOcode P419 FINISHED
Object KAUG
KAUG is the ICAO airport code for Augusta State Airport, a public airport serving Augusta, Maine, in the United States.
 E245608 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: KAUG | Statement: [Augusta State Airport, ICAOcode, KAUG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KAUG
Context triple: [Augusta State Airport, ICAOcode, KAUG]
  • A. KA
    KA is the vehicle registration code used on license plates for cars registered in the German city of Karlsruhe.
  • B. KCA
    KCA is a nonprofit organization dedicated to providing life-saving HIV treatment, care, and support to children and families in underserved communities, particularly in Africa and India.
  • C. Ka
    Ka was an early ancient Egyptian king of the First Dynasty period, known from tomb inscriptions at Abydos and considered one of the first rulers to use a royal serekh.
  • D. KAZ
    KAZ is the three-letter ISO 3166-1 alpha-3 country code assigned to Kazakhstan for international standardization and identification.
  • E. Kaag
    Kaag is a small Dutch village in South Holland known for its island setting in the Kagerplassen lake area and its traditional water sports and boating culture.
  • 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: KAUG
Triple: [Augusta State Airport, ICAOcode, KAUG]
Generated description
KAUG is the ICAO airport code for Augusta State Airport, a public airport serving Augusta, Maine, in the United States.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KAUG
Target entity description: KAUG is the ICAO airport code for Augusta State Airport, a public airport serving Augusta, Maine, in the United States.
  • A. KA
    KA is the vehicle registration code used on license plates for cars registered in the German city of Karlsruhe.
  • B. KCA
    KCA is a nonprofit organization dedicated to providing life-saving HIV treatment, care, and support to children and families in underserved communities, particularly in Africa and India.
  • C. Ka
    Ka was an early ancient Egyptian king of the First Dynasty period, known from tomb inscriptions at Abydos and considered one of the first rulers to use a royal serekh.
  • D. KAZ
    KAZ is the three-letter ISO 3166-1 alpha-3 country code assigned to Kazakhstan for international standardization and identification.
  • E. Kaag
    Kaag is a small Dutch village in South Holland known for its island setting in the Kagerplassen lake area and its traditional water sports and boating culture.
  • 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_69a88b06709c8190978fb2418470d1b6 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abbfeb889081908cddf58a57b216df completed March 7, 2026, 6:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae655045d081909b8294ec706e0814 completed March 9, 2026, 6:14 a.m.
NEDg Description generation batch_69ae662f689881908ecd76952b78f863 completed March 9, 2026, 6:18 a.m.
NED2 Entity disambiguation (via description) batch_69ae668ef8bc819085ed1c83f447d396 completed March 9, 2026, 6:19 a.m.
Created at: March 4, 2026, 7:46 p.m.