Triple

T6862478
Position Surface form Disambiguated ID Type / Status
Subject Essendon Airport E158314 entity
Predicate IATAcode P418 FINISHED
Object MEB
MEB is the IATA airport code for Essendon Airport, a public airport serving the Melbourne region in Victoria, Australia.
 E624396 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: MEB | Statement: [Essendon Airport, IATAcode, MEB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MEB
Context triple: [Essendon Airport, IATAcode, MEB]
  • A. MEI
    MEI is the vehicle registration code for the German town of Meissen in the state of Saxony.
  • B. MEI
    MEI is a climate index that quantifies the strength and phase of the El Niño–Southern Oscillation by combining multiple atmospheric and oceanic variables over the tropical Pacific.
  • C. MOE
    MOE is the common abbreviation for Japan’s Ministry of Education, the government body responsible for national education policy and administration.
  • D. MOE
    MOE is the government ministry responsible for overseeing and administering the national education system in South Korea.
  • E. MOE
    MOE is the Ministry of Education of the Republic of China (Taiwan), the government agency responsible for national education policy and administration.
  • 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: MEB
Triple: [Essendon Airport, IATAcode, MEB]
Generated description
MEB is the IATA airport code for Essendon Airport, a public airport serving the Melbourne region in Victoria, Australia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MEB
Target entity description: MEB is the IATA airport code for Essendon Airport, a public airport serving the Melbourne region in Victoria, Australia.
  • A. MEI
    MEI is the vehicle registration code for the German town of Meissen in the state of Saxony.
  • B. MEI
    MEI is a climate index that quantifies the strength and phase of the El Niño–Southern Oscillation by combining multiple atmospheric and oceanic variables over the tropical Pacific.
  • C. MOE
    MOE is the common abbreviation for Japan’s Ministry of Education, the government body responsible for national education policy and administration.
  • D. MOE
    MOE is the government ministry responsible for overseeing and administering the national education system in South Korea.
  • E. MOE
    MOE is the Ministry of Education of the Republic of China (Taiwan), the government agency responsible for national education policy and administration.
  • 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_69c68830cdbc8190a8301c7a9d9f651a completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d887d6648190a0c2d1cb1b284bfe completed March 27, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c72fed3e788190b2b68fc93173f73e completed March 28, 2026, 1:33 a.m.
NEDg Description generation batch_69c7361177ac8190b1e06cb15d258d0f completed March 28, 2026, 1:59 a.m.
NED2 Entity disambiguation (via description) batch_69c7381015a081909f9b32732f826d2c completed March 28, 2026, 2:08 a.m.
Created at: March 27, 2026, 2:21 p.m.