Triple

T1342923
Position Surface form Disambiguated ID Type / Status
Subject Maryland Department of Agriculture E28505 entity
Predicate hasAbbreviation P43 FINISHED
Object MDA
MDA is the state agency responsible for promoting and regulating Maryland’s agricultural industry, including farming, food safety, and related environmental programs.
 E154040 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: MDA | Statement: [Maryland Department of Agriculture, hasAbbreviation, MDA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MDA
Context triple: [Maryland Department of Agriculture, hasAbbreviation, MDA]
  • 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. MDOA
    MDOA is the state agency responsible for advocating for and providing services to older adults and their caregivers in Maryland.
  • E. 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.
  • 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: MDA
Triple: [Maryland Department of Agriculture, hasAbbreviation, MDA]
Generated description
MDA is the state agency responsible for promoting and regulating Maryland’s agricultural industry, including farming, food safety, and related environmental programs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MDA
Target entity description: MDA is the state agency responsible for promoting and regulating Maryland’s agricultural industry, including farming, food safety, and related environmental programs.
  • 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. MDOA
    MDOA is the state agency responsible for advocating for and providing services to older adults and their caregivers in Maryland.
  • E. 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.
  • 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_69a49854eb3481908c7d56b2e449a290 completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c2174d048190a6e9380df302265f completed March 1, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc632cbc88190a64897f1b101c699 completed March 8, 2026, 12:43 a.m.
NEDg Description generation batch_69acc6dbd80881908d640ee204ce9a12 completed March 8, 2026, 12:46 a.m.
NED2 Entity disambiguation (via description) batch_69acc8199f508190a86c18ad9085d341 completed March 8, 2026, 12:51 a.m.
Created at: March 1, 2026, 7:56 p.m.