Triple

T1377213
Position Surface form Disambiguated ID Type / Status
Subject European Union economic and monetary union E29252 entity
Predicate alsoKnownAs P39 FINISHED
Object EMU
EMU is the European Union’s framework for coordinating economic policy and managing the single currency, the euro, among participating member states.
 E158737 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: EMU | Statement: [European Union economic and monetary union, alsoKnownAs, EMU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: EMU
Context triple: [European Union economic and monetary union, alsoKnownAs, EMU]
  • A. EMD
    EMD is the commonly used abbreviation for the Engineering Management Division, a professional group focused on the practice and advancement of engineering management.
  • B. EA
    EA is the commonly used abbreviation for the Environment Agency, the public body responsible for environmental protection and regulation in England.
  • C. Metro
    Metro is the rapid transit system serving the Washington, D.C. metropolitan area, operated by the Washington Metropolitan Area Transit Authority (WMATA).
  • D. Metro
    Metro is the primary public transportation agency serving Los Angeles County, operating buses, light rail, subway, and other transit services across the region.
  • E. ENA
    ENA is a prestigious French grande école that trained many of the country’s top civil servants and political leaders.
  • 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: EMU
Triple: [European Union economic and monetary union, alsoKnownAs, EMU]
Generated description
EMU is the European Union’s framework for coordinating economic policy and managing the single currency, the euro, among participating member states.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: EMU
Target entity description: EMU is the European Union’s framework for coordinating economic policy and managing the single currency, the euro, among participating member states.
  • A. EMD
    EMD is the commonly used abbreviation for the Engineering Management Division, a professional group focused on the practice and advancement of engineering management.
  • B. EMD
    EMD is the vehicle registration code assigned to the German town of Emden.
  • C. EA
    EA is the commonly used abbreviation for the Environment Agency, the public body responsible for environmental protection and regulation in England.
  • D. Metro
    Metro is the primary public transportation agency serving Los Angeles County, operating buses, light rail, subway, and other transit services across the region.
  • E. Metro
    Metro is the rapid transit system serving the Washington, D.C. metropolitan area, operated by the Washington Metropolitan Area Transit Authority (WMATA).
  • 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_69a498d883a48190bfdca525296ef7ee completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c31602b8819087a57e8d390cae7a completed March 1, 2026, 10:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69acd488698481909411c004aadfcaec completed March 8, 2026, 1:44 a.m.
NEDg Description generation batch_69acd625592481908c688802ce8381ee completed March 8, 2026, 1:51 a.m.
NED2 Entity disambiguation (via description) batch_69acd6daf83881909cf5a4105ebf14a5 completed March 8, 2026, 1:54 a.m.
Created at: March 1, 2026, 7:59 p.m.