Triple

T20776223
Position Surface form Disambiguated ID Type / Status
Subject Market Access Group E511360 entity
Predicate abbreviation P43 FINISHED
Object MAG
MAG is a business consultancy specializing in helping companies navigate market access, pricing, and reimbursement strategies for their products and services.
E1449522 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: MAG | Statement: [Market Access Group, abbreviation, MAG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MAG
Context triple: [Market Access Group, abbreviation, MAG]
  • A. MAG
    MAG is a major British airport operator that owns and manages several UK airports, including Manchester Airport.
  • B. MAG
    MAG is the magnetometer instrument aboard the European Space Agency’s Venus Express spacecraft, designed to measure Venus’s magnetic field and its interaction with the solar wind.
  • C. MAG
    MAG is the National Rail station code for Maghull railway station in Merseyside, England.
  • D. MAG
    MAG is the standard abbreviation for a United States Marine Corps aviation unit known as a Marine Aircraft Group.
  • E. MAG
    MAG is the abbreviated name used to represent Magic Gaming, the NBA 2K League affiliate of the Orlando Magic.
  • 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: MAG
Triple: [Market Access Group, abbreviation, MAG]
Generated description
MAG is a business consultancy specializing in helping companies navigate market access, pricing, and reimbursement strategies for their products and services.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: MAG
Target entity description: MAG is a business consultancy specializing in helping companies navigate market access, pricing, and reimbursement strategies for their products and services.
  • A. MAG
    MAG is the parent company of Malaysia Airlines and related aviation businesses, overseeing the group’s airline, cargo, and aviation services operations.
  • B. MAG
    MAG is the Multistakeholder Advisory Group that supports and advises the United Nations-convened Internet Governance Forum on its program and agenda.
  • C. MAG
    MAG is an international humanitarian organization that works to clear landmines and unexploded ordnance and make land safe for communities affected by conflict.
  • D. MAG
    MAG is a major British airport operator that owns and manages several UK airports, including Manchester Airport.
  • E. MAG
    MAG is the standard abbreviation for a United States Marine Corps aviation unit known as a Marine Aircraft Group.
  • 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_69e0b4cac7a48190a715cb3d545df2b4 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c26b06ac81909aef3b0a0ad79a33 completed April 21, 2026, 12:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a08ef95f3d0819088cab88673d49c28 completed May 16, 2026, 10:28 p.m.
NEDg Description generation batch_6a08f015f37081909e7202a76a5814ea completed May 16, 2026, 10:30 p.m.
NED2 Entity disambiguation (via description) batch_6a08f07dfb208190b00ad28d62e21de4 completed May 16, 2026, 10:32 p.m.
Created at: April 16, 2026, 12:37 p.m.