Triple

T1711972
Position Surface form Disambiguated ID Type / Status
Subject Elliptic Curve Cryptography E37202 entity
Predicate abbreviation P43 FINISHED
Object ECC
ECC is a public-key cryptography approach that uses the mathematics of elliptic curves to provide strong security with relatively small key sizes.
 E192661 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: ECC | Statement: [Elliptic Curve Cryptography, abbreviation, ECC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ECC
Context triple: [Elliptic Curve Cryptography, abbreviation, ECC]
  • A. ECC
    ECC is the National Rail station code for Eccles railway station in Greater Manchester, England.
  • B. ECCAS
    ECCAS (Economic Community of Central African States) is a regional economic community that promotes economic integration, peace, and development among Central African countries.
  • C. ECA
    The Economic Cooperation Administration (ECA) was the U.S. government agency responsible for administering the Marshall Plan to aid European economic recovery after World War II.
  • D. ECA
    ECA is a regional United Nations commission focused on promoting economic and social development across the African continent.
  • E. ECA
    The ECA is the European Union institution responsible for auditing the EU’s finances and ensuring that its budget is correctly implemented.
  • 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: ECC
Triple: [Elliptic Curve Cryptography, abbreviation, ECC]
Generated description
ECC is a public-key cryptography approach that uses the mathematics of elliptic curves to provide strong security with relatively small key sizes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ECC
Target entity description: ECC is a public-key cryptography approach that uses the mathematics of elliptic curves to provide strong security with relatively small key sizes.
  • A. ECC
    ECC is the National Rail station code for Eccles railway station in Greater Manchester, England.
  • B. ECCAS
    ECCAS (Economic Community of Central African States) is a regional economic community that promotes economic integration, peace, and development among Central African countries.
  • C. ECA
    The Economic Cooperation Administration (ECA) was the U.S. government agency responsible for administering the Marshall Plan to aid European economic recovery after World War II.
  • D. ECA
    ECA is a regional United Nations commission focused on promoting economic and social development across the African continent.
  • E. ECA
    The ECA is the European Union institution responsible for auditing the EU’s finances and ensuring that its budget is correctly implemented.
  • 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_69a8861912dc8190931af43b4b9158a7 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa6315afdc81908409435bb47e8ee0 completed March 6, 2026, 5:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad8addf4a48190b19cdb861db5eecd completed March 8, 2026, 2:42 p.m.
NEDg Description generation batch_69ad957adf1c8190b7c8656c1984f998 completed March 8, 2026, 3:27 p.m.
NED2 Entity disambiguation (via description) batch_69ad97af6b388190b2af293599108df3 completed March 8, 2026, 3:37 p.m.
Created at: March 4, 2026, 7:30 p.m.