Triple

T1159266
Position Surface form Disambiguated ID Type / Status
Subject Electronic Frontier Foundation E24458 entity
Predicate abbreviation P43 FINISHED
Object EFF
EFF is a leading nonprofit organization that defends civil liberties, privacy, and free expression in the digital world.
 E131667 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: EFF | Statement: [Electronic Frontier Foundation, abbreviation, EFF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: EFF
Context triple: [Electronic Frontier Foundation, abbreviation, EFF]
  • A. EEF
    EEF is the abbreviation for the Economist Educational Foundation, a charity that promotes economic and financial literacy through educational resources and programs.
  • B. FFF
    FFF is a global youth-led climate movement advocating for urgent action against climate change through school strikes and public demonstrations.
  • C. CEF
    CEF is the abbreviation for the Canadian Expeditionary Force, the field force of the Canadian Army raised for service overseas during the First World War.
  • D. EMA
    EMA is the European Union’s regulatory authority responsible for the scientific evaluation, supervision, and safety monitoring of medicines.
  • E. FEC
    FEC is the independent U.S. regulatory agency responsible for enforcing federal campaign finance laws and overseeing the financing of elections for federal office.
  • 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: EFF
Triple: [Electronic Frontier Foundation, abbreviation, EFF]
Generated description
EFF is a leading nonprofit organization that defends civil liberties, privacy, and free expression in the digital world.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: EFF
Target entity description: EFF is a leading nonprofit organization that defends civil liberties, privacy, and free expression in the digital world.
  • A. EEF
    EEF is the abbreviation for the Economist Educational Foundation, a charity that promotes economic and financial literacy through educational resources and programs.
  • B. FFF
    FFF is a global youth-led climate movement advocating for urgent action against climate change through school strikes and public demonstrations.
  • C. CEF
    CEF is the abbreviation for the Canadian Expeditionary Force, the field force of the Canadian Army raised for service overseas during the First World War.
  • D. EMA
    EMA is the European Union’s regulatory authority responsible for the scientific evaluation, supervision, and safety monitoring of medicines.
  • E. FEC
    FEC is the independent U.S. regulatory agency responsible for enforcing federal campaign finance laws and overseeing the financing of elections for federal office.
  • 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_69a494060e148190abb42f971242c197 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bcad47a08190895769611798f67f completed March 1, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac5ebbf80881909010e1e1e59212d4 completed March 7, 2026, 5:22 p.m.
NEDg Description generation batch_69ac5f77286c81908267706202ab032f completed March 7, 2026, 5:25 p.m.
NED2 Entity disambiguation (via description) batch_69ac5fe000bc81909c1131b8c1f1db6b completed March 7, 2026, 5:26 p.m.
Created at: March 1, 2026, 7:45 p.m.