Triple

T20852770
Position Surface form Disambiguated ID Type / Status
Subject Market Abuse Regulation E513404 entity
Predicate shortName P43 FINISHED
Object MAR
MAR is the commonly used abbreviation for the European Union’s Market Abuse Regulation, a legal framework designed to prevent insider dealing, market manipulation, and other forms of market abuse in financial markets.
 E1453979 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: MAR | Statement: [Market Abuse Regulation, shortName, MAR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MAR
Context triple: [Market Abuse Regulation, shortName, MAR]
  • A. MAR
    MAR is the three-letter ISO 3166-1 alpha-3 country code assigned to Morocco.
  • B. MAR
    MAR is the stock ticker symbol for Marriott International, a leading global hotel and lodging company.
  • C. Ma
    Ma is a fictional character appearing in Enid Blyton’s children’s adventure novel "The Circus of Adventure."
  • D. Ma
    "Ma" is a track from the album "Masterpiece," likely contributing to the record's overall artistic and musical identity.
  • E. Ma
    Ma is an ancient Anatolian mother and warrior goddess associated with fertility, protection, and local cult worship in regions such as Comana.
  • 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: MAR
Triple: [Market Abuse Regulation, shortName, MAR]
Generated description
MAR is the commonly used abbreviation for the European Union’s Market Abuse Regulation, a legal framework designed to prevent insider dealing, market manipulation, and other forms of market abuse in financial markets.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MAR
Target entity description: MAR is the commonly used abbreviation for the European Union’s Market Abuse Regulation, a legal framework designed to prevent insider dealing, market manipulation, and other forms of market abuse in financial markets.
  • A. MAR
    MAR is the three-letter ISO 3166-1 alpha-3 country code assigned to Morocco.
  • B. MAR
    MAR is the stock ticker symbol for Marriott International, a leading global hotel and lodging company.
  • C. Ma
    Ma is a fictional character appearing in Enid Blyton’s children’s adventure novel "The Circus of Adventure."
  • D. Ma
    "Ma" is a track from the album "Masterpiece," likely contributing to the record's overall artistic and musical identity.
  • E. Ma
    Ma is an ancient Anatolian mother and warrior goddess associated with fertility, protection, and local cult worship in regions such as Comana.
  • 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_69e0b4f4898081908209e58edb8f9c45 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c3a4df5c8190aa0e7684ad6fc9f2 completed April 21, 2026, 12:24 a.m.
NED1 Entity disambiguation (via context triple) batch_6a090b0980f48190a2dc1cc29621bcd8 completed May 17, 2026, 12:25 a.m.
NEDg Description generation batch_6a090bf30e048190a2c81dece02c997d completed May 17, 2026, 12:29 a.m.
NED2 Entity disambiguation (via description) batch_6a090d0d52fc8190aed0a475f3424213 completed May 17, 2026, 12:34 a.m.
Created at: April 16, 2026, 12:44 p.m.