Triple

T20154688
Position Surface form Disambiguated ID Type / Status
Subject Helen Morse E491524 entity
Predicate notableWork P4 FINISHED
Object MDA
MDA is an Australian television drama series in which Helen Morse played a significant role.
E1414971 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: [Helen Morse, notableWork, MDA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MDA
Context triple: [Helen Morse, notableWork, 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. MDA
    MDA is a Canadian space technology company known for developing advanced satellite systems, robotics, and Earth observation solutions.
  • D. MDA
    MDA is the common abbreviation for the Mighty Ducks of Anaheim, a former National Hockey League team based in Anaheim, California.
  • E. MDA
    MDA (Model-Driven Architecture) is a software design approach that emphasizes creating and transforming high-level platform-independent models into platform-specific implementations, standardized by the Object Management Group.
  • 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: [Helen Morse, notableWork, MDA]
Generated description
MDA is an Australian television drama series in which Helen Morse played a significant role.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: MDA
Target entity description: MDA is an Australian television drama series in which Helen Morse played a significant role.
  • A. MDA
    MDA is a Canadian space technology company known for developing advanced satellite systems, robotics, and Earth observation solutions.
  • B. MDA
    MDA is the common abbreviation for the Mighty Ducks of Anaheim, a former National Hockey League team based in Anaheim, California.
  • C. MDA
    MDA is the state agency responsible for promoting and regulating Maryland’s agricultural industry, including farming, food safety, and related environmental programs.
  • D. MDA
    MDA is the ICAO airline designator assigned to Mandarin Airlines, a Taiwanese regional carrier.
  • E. MDA
    MDA is the United States Missile Defense Agency, a Department of Defense organization responsible for developing and deploying systems to defend the U.S. and its allies against ballistic missile threats.
  • 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_69da6265f8f0819080b29c752a574088 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e667df7ac081908816d2d29e7c6513 completed April 20, 2026, 5:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0834743ea88190a30384ab16826485 completed May 16, 2026, 9:10 a.m.
NEDg Description generation batch_6a0835cfd5548190bd29237b0cc08b9e completed May 16, 2026, 9:16 a.m.
NED2 Entity disambiguation (via description) batch_6a083666e9188190b5c62e2f0e7b123e completed May 16, 2026, 9:18 a.m.
Created at: April 11, 2026, 11:34 p.m.