Triple

T5341078
Position Surface form Disambiguated ID Type / Status
Subject U.S. military health system E123945 entity
Predicate abbreviation P43 FINISHED
Object MHS
MHS is the acronym for the U.S. Military Health System, the organization that provides healthcare services to active-duty service members, retirees, and their families.
 E512126 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: MHS | Statement: [U.S. military health system, abbreviation, MHS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MHS
Context triple: [U.S. military health system, abbreviation, MHS]
  • A. MSH
    MSH is the vehicle registration code for the Mansfeld-Südharz district in the German state of Saxony-Anhalt.
  • B. MHSC
    MHSC is the commonly used abbreviation for Montpellier Hérault Sport Club, a French professional football club based in Montpellier.
  • C. CMH
    CMH is the IATA airport code for John Glenn Columbus International Airport, the primary commercial airport serving Columbus, Ohio.
  • D. 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.
  • E. MDH
    MDH is the acronym for the Maryland Department of Health, the state agency responsible for public health services, policy, and regulation in Maryland.
  • 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: MHS
Triple: [U.S. military health system, abbreviation, MHS]
Generated description
MHS is the acronym for the U.S. Military Health System, the organization that provides healthcare services to active-duty service members, retirees, and their families.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MHS
Target entity description: MHS is the acronym for the U.S. Military Health System, the organization that provides healthcare services to active-duty service members, retirees, and their families.
  • A. MSH
    MSH is the vehicle registration code for the Mansfeld-Südharz district in the German state of Saxony-Anhalt.
  • B. MHSC
    MHSC is the commonly used abbreviation for Montpellier Hérault Sport Club, a French professional football club based in Montpellier.
  • C. CMH
    CMH is the IATA airport code for John Glenn Columbus International Airport, the primary commercial airport serving Columbus, Ohio.
  • D. MDH
    MDH is the acronym for the Maryland Department of Health, the state agency responsible for public health services, policy, and regulation in Maryland.
  • E. 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.
  • 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_69bd464b07f8819095aa76577c9829e4 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd85cb250c81908a48e4e2bbebbdb9 completed March 20, 2026, 5:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf18c8db388190a31f55854e7370fc completed March 21, 2026, 10:16 p.m.
NEDg Description generation batch_69bf19c8273081908a5138e9af921ec7 completed March 21, 2026, 10:20 p.m.
NED2 Entity disambiguation (via description) batch_69bf1a3049648190b5040e587671610a completed March 21, 2026, 10:22 p.m.
Created at: March 20, 2026, 2 p.m.