Triple

T2303654
Position Surface form Disambiguated ID Type / Status
Subject Middle Georgia State University E51787 entity
Predicate abbreviation P43 FINISHED
Object MGA
MGA is a public university in Georgia, United States, offering a range of undergraduate and graduate programs across multiple campuses.
 E253408 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: MGA | Statement: [Middle Georgia State University, abbreviation, MGA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MGA
Context triple: [Middle Georgia State University, abbreviation, MGA]
  • A. MGA
    MGA is the commonly used abbreviation for the Maryland General Assembly, the state’s bicameral legislative body.
  • B. Ma$e
    Ma$e is an American rapper and songwriter known for his late-1990s success with Bad Boy Records and his smooth, laid-back delivery on hits like "Feel So Good."
  • C. MG
    MG is a historic British automotive marque best known for its sports cars, now owned and produced by Chinese manufacturer SAIC Motor.
  • D. MGM
    MGM (Metro-Goldwyn-Mayer) is a historic American film studio renowned for its iconic roaring lion logo and for producing many of the most famous movies of Hollywood’s Golden Age.
  • E. MGM
    MGM is a major American entertainment and hospitality brand best known for its iconic casinos, resorts, and film studio legacy.
  • 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: MGA
Triple: [Middle Georgia State University, abbreviation, MGA]
Generated description
MGA is a public university in Georgia, United States, offering a range of undergraduate and graduate programs across multiple campuses.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MGA
Target entity description: MGA is a public university in Georgia, United States, offering a range of undergraduate and graduate programs across multiple campuses.
  • A. MGA
    MGA is the commonly used abbreviation for the Maryland General Assembly, the state’s bicameral legislative body.
  • B. Ma$e
    Ma$e is an American rapper and songwriter known for his late-1990s success with Bad Boy Records and his smooth, laid-back delivery on hits like "Feel So Good."
  • C. MG
    MG is a historic British automotive marque best known for its sports cars, now owned and produced by Chinese manufacturer SAIC Motor.
  • D. MGM
    MGM (Metro-Goldwyn-Mayer) is a historic American film studio renowned for its iconic roaring lion logo and for producing many of the most famous movies of Hollywood’s Golden Age.
  • E. MGM
    MGM is a major American entertainment and hospitality brand best known for its iconic casinos, resorts, and film studio legacy.
  • 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_69a88b0a9f248190bcff941463d8f65a completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc5f2de7c819095bd74a551d8ff18 completed March 7, 2026, 6:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae7f332e788190b1dd4b8b0bbfe5d7 completed March 9, 2026, 8:05 a.m.
NEDg Description generation batch_69ae802a066881909aa4e7b00e29306f completed March 9, 2026, 8:09 a.m.
NED2 Entity disambiguation (via description) batch_69ae80c37ff48190a24b7806320ebc00 completed March 9, 2026, 8:11 a.m.
Created at: March 4, 2026, 7:49 p.m.