Triple

T1258760
Position Surface form Disambiguated ID Type / Status
Subject Public Law 93-438 E12450 entity
Predicate region 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: [Public Law 93-438, region, United States]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: United States
Context triple: [Public Law 93-438, region, 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_69a4933352e08190ac617291985e76c0 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4bfc3a2848190891e73b351019d5b completed March 1, 2026, 10:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac996dcd3481909543f1b9758a0f91 completed March 7, 2026, 9:32 p.m.
Created at: March 1, 2026, 7:50 p.m.