Triple

T2081234
Position Surface form Disambiguated ID Type / Status
Subject Myra, West Virginia E45246 entity
Predicate partOf P40 FINISHED
Object United States E14 NE FINISHED

How this triple was built (2 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: United States | Statement: [Myra, West Virginia, partOf, United States]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: United States
Context triple: [Myra, West Virginia, partOf, United States]
  • A. United States of America chosen
    The United States of America is a large federal republic in North America known for its global political, economic, military, and cultural influence.
  • B. EUA
    EUA (European University Association) is a major organization representing and supporting higher education institutions and national rectors’ conferences across Europe in areas such as policy, quality assurance, and institutional development.
  • C. America
    America is the landmass in the Western Hemisphere comprising the continents of North and South America, widely recognized for its vast geographic, cultural, and political diversity.
  • D. US
    US is the IATA airline designator code assigned to the former American airline US Airways.
  • E. Amerika
    Amerika is a novel by Franz Kafka that follows a young European immigrant’s surreal and often absurd experiences in the United States.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a8891869c88190a02643e3bb746f59 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abba35c2588190933dba882f52dd17 completed March 7, 2026, 5:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae71968eb481908271b05e7a8b0588 completed March 9, 2026, 7:07 a.m.
Created at: March 4, 2026, 7:41 p.m.