Triple

T16405477
Position Surface form Disambiguated ID Type / Status
Subject Malaysia Airports Holdings Berhad E398413 entity
Predicate tickerSymbol P1447 FINISHED
Object MAHB
MAHB is a Malaysian airport operator that manages and develops most of the country’s major airports, including Kuala Lumpur International Airport.
 E1212577 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: MAHB | Statement: [Malaysia Airports Holdings Berhad, tickerSymbol, MAHB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MAHB
Context triple: [Malaysia Airports Holdings Berhad, tickerSymbol, MAHB]
  • A. MAB
    MAB is a German bibliographic data format used for cataloging and exchanging library records, closely related to and historically aligned with MARC standards.
  • B. MAB
    MAB is a German vehicle registration code used for cars registered in the Erzgebirgskreis district of Saxony.
  • C. MAB
    MAB is the London Stock Exchange ticker symbol for Mitchells & Butlers plc, a major UK operator of pubs, bars, and restaurants.
  • D. MUHBA
    MUHBA is Barcelona’s city history museum, dedicated to preserving and showcasing the urban, archaeological, and cultural heritage of Barcelona.
  • E. MCHB
    MCHB is the commonly used abbreviation for the Maternal and Child Health Bureau, a U.S. federal agency focused on improving the health and well-being of mothers, children, and families.
  • 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: MAHB
Triple: [Malaysia Airports Holdings Berhad, tickerSymbol, MAHB]
Generated description
MAHB is a Malaysian airport operator that manages and develops most of the country’s major airports, including Kuala Lumpur International Airport.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MAHB
Target entity description: MAHB is a Malaysian airport operator that manages and develops most of the country’s major airports, including Kuala Lumpur International Airport.
  • A. MAB
    MAB is a German bibliographic data format used for cataloging and exchanging library records, closely related to and historically aligned with MARC standards.
  • B. MAB
    MAB is the London Stock Exchange ticker symbol for Mitchells & Butlers plc, a major UK operator of pubs, bars, and restaurants.
  • C. MAB
    MAB is a German vehicle registration code used for cars registered in the Erzgebirgskreis district of Saxony.
  • D. MUHBA
    MUHBA is Barcelona’s city history museum, dedicated to preserving and showcasing the urban, archaeological, and cultural heritage of Barcelona.
  • E. MCHB
    MCHB is the commonly used abbreviation for the Maternal and Child Health Bureau, a U.S. federal agency focused on improving the health and well-being of mothers, children, and families.
  • 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_69d87f2950248190bc8ad9b9bebdc8c8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e327d2b4e48190b7153f198639e9cd completed April 18, 2026, 6:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a003c62614c8190acd6d211cab1be11 completed May 10, 2026, 8:05 a.m.
NEDg Description generation batch_6a003dc6f4888190ae326c9606d2a674 completed May 10, 2026, 8:11 a.m.
NED2 Entity disambiguation (via description) batch_6a0041842cc88190b81432d234f9aa17 completed May 10, 2026, 8:27 a.m.
Created at: April 10, 2026, 5:09 a.m.