Triple

T6467667
Position Surface form Disambiguated ID Type / Status
Subject Maryland Department of Health E142269 entity
Predicate abbreviation P43 FINISHED
Object MDH E142269 NE FINISHED

How this triple was built (2 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: MDH | Statement: [Maryland Department of Health, abbreviation, MDH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MDH
Context triple: [Maryland Department of Health, abbreviation, MDH]
  • A. MDH chosen
    MDH is the acronym for the Maryland Department of Health, the state agency responsible for public health services, policy, and regulation in Maryland.
  • B. MDH
    MDH is the commonly used abbreviation for the Faculty of Medicine, Dentistry and Health, an academic division focused on education and research in medical, dental and health sciences.
  • C. MDC
    MDC is a Zimbabwean opposition political party known as the Movement for Democratic Change, which has played a major role in challenging the long-standing rule of ZANU–PF.
  • D. MDU
    MDU is the official county code used to identify Madera County in administrative and governmental contexts.
  • E. MDV
    MDV is a venture capital firm known for investing in early-stage technology and life sciences companies.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c008d3bf4c8190bcf798c5ba9d6fb3 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06a1461f08190b75f97c0bb3b0be6 completed March 22, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64bed24b881909ade4e5451153986 completed March 27, 2026, 9:20 a.m.
Created at: March 22, 2026, 4:49 p.m.