Triple

T1279047
Position Surface form Disambiguated ID Type / Status
Subject Maryland Department of the Environment E27280 entity
Predicate abbreviation P43 FINISHED
Object MDE
MDE is the state agency in Maryland responsible for protecting and restoring the environment and public health through regulation, monitoring, and enforcement of environmental laws.
E147021 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: MDE | Statement: [Maryland Department of the Environment, abbreviation, MDE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MDE
Context triple: [Maryland Department of the Environment, abbreviation, MDE]
  • A. MDA
    MDA (Monochrome Display Adapter) is IBM's original text-only video display standard for early IBM PCs, providing high-resolution monochrome output without graphics capabilities.
  • B. MDA
    MDA is the three-letter ISO 3166-1 alpha-3 country code representing the Republic of Moldova.
  • C. MAD
    MAD is the three-letter IATA airport code for Adolfo Suárez Madrid–Barajas Airport, the main international airport serving Madrid, Spain.
  • D. MDT
    MDT is the stock ticker symbol for Medtronic, a leading global medical technology company specializing in devices and therapies for chronic diseases.
  • E. MDU
    MDU is the official county code used to identify Madera County in administrative and governmental contexts.
  • 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: MDE
Triple: [Maryland Department of the Environment, abbreviation, MDE]
Generated description
MDE is the state agency in Maryland responsible for protecting and restoring the environment and public health through regulation, monitoring, and enforcement of environmental laws.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: MDE
Target entity description: MDE is the state agency in Maryland responsible for protecting and restoring the environment and public health through regulation, monitoring, and enforcement of environmental laws.
  • A. MDA
    MDA (Monochrome Display Adapter) is IBM's original text-only video display standard for early IBM PCs, providing high-resolution monochrome output without graphics capabilities.
  • B. MDA
    MDA is the three-letter ISO 3166-1 alpha-3 country code representing the Republic of Moldova.
  • C. MAD
    MAD is the three-letter IATA airport code for Adolfo Suárez Madrid–Barajas Airport, the main international airport serving Madrid, Spain.
  • D. MDT
    MDT is the stock ticker symbol for Medtronic, a leading global medical technology company specializing in devices and therapies for chronic diseases.
  • E. MDU
    MDU is the official county code used to identify Madera County in administrative and governmental contexts.
  • 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_69a496d3710c8190955dee8bc0dacb50 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c092eb688190bf42bbd59e4ff289 completed March 1, 2026, 10:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69aca2f91b348190b2994af7edaf4f67 completed March 7, 2026, 10:13 p.m.
NEDg Description generation batch_69aca3ee6d748190bb5b214471f5c191 completed March 7, 2026, 10:17 p.m.
NED2 Entity disambiguation (via description) batch_69aca44c41908190981d4ccdcaa7b613 completed March 7, 2026, 10:18 p.m.
Created at: March 1, 2026, 7:50 p.m.