Triple

T1021790
Position Surface form Disambiguated ID Type / Status
Subject Risk Management Agency E22054 entity
Predicate abbreviation P43 FINISHED
Object RMA
RMA is a U.S. Department of Agriculture agency responsible for overseeing federal crop insurance and risk management programs for farmers and ranchers.
 E121757 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: RMA | Statement: [Risk Management Agency, abbreviation, RMA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: RMA
Context triple: [Risk Management Agency, abbreviation, RMA]
  • A. RM
    RM is the currency symbol that was used to denote the German Reichsmark, the former official currency of Germany from 1924 to 1948.
  • B. RAC
    RAC is the abbreviation for the Royal African Company, a 17th- and 18th-century English trading company heavily involved in the transatlantic slave trade.
  • C. RA
    RA is a prestigious post-nominal title indicating membership as a Royal Academician of the Royal Academy of Arts in London.
  • D. RA
    RA is the commonly used abbreviation for the Royal Regiment of Artillery, a principal artillery branch of the British Army.
  • E. RAD
    RAD is a radiation assessment detector aboard NASA's Curiosity rover that measures high-energy particles on Mars’ surface to evaluate the planet’s radiation environment and its implications for future human exploration.
  • 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: RMA
Triple: [Risk Management Agency, abbreviation, RMA]
Generated description
RMA is a U.S. Department of Agriculture agency responsible for overseeing federal crop insurance and risk management programs for farmers and ranchers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: RMA
Target entity description: RMA is a U.S. Department of Agriculture agency responsible for overseeing federal crop insurance and risk management programs for farmers and ranchers.
  • A. RM
    RM is the currency symbol that was used to denote the German Reichsmark, the former official currency of Germany from 1924 to 1948.
  • B. RAC
    RAC is the abbreviation for the Royal African Company, a 17th- and 18th-century English trading company heavily involved in the transatlantic slave trade.
  • C. RA
    RA is a prestigious post-nominal title indicating membership as a Royal Academician of the Royal Academy of Arts in London.
  • D. RA
    RA is the commonly used abbreviation for the Royal Regiment of Artillery, a principal artillery branch of the British Army.
  • E. RAD
    RAD is a radiation assessment detector aboard NASA's Curiosity rover that measures high-energy particles on Mars’ surface to evaluate the planet’s radiation environment and its implications for future human exploration.
  • 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_69a493d6e380819097b384986ffc315c completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b7dead9c8190a0f8d4ef48e6c809 completed March 1, 2026, 10:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac3bb63f14819098f5e32af3b98508 completed March 7, 2026, 2:52 p.m.
NEDg Description generation batch_69ac3de4fbb88190855cf92af51fe70b completed March 7, 2026, 3:01 p.m.
NED2 Entity disambiguation (via description) batch_69ac3e45d9e88190bc88d037c00c3ecc completed March 7, 2026, 3:03 p.m.
Created at: March 1, 2026, 7:41 p.m.