Triple

T4866077
Position Surface form Disambiguated ID Type / Status
Subject Federal Home Loan Bank of Seattle E108772 entity
Predicate regionServed P82 FINISHED
Object Washington E20479 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: Washington | Statement: [Federal Home Loan Bank of Seattle, regionServed, Washington]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Washington
Context triple: [Federal Home Loan Bank of Seattle, regionServed, Washington]
  • A. Washington chosen
    Washington is a U.S. state in the Pacific Northwest known for its diverse landscapes, technology industry centered around Seattle, and significant cultural and economic influence on the West Coast.
  • B. Washington
    Washington is a common English surname most famously borne by George Washington, the first president of the United States.
  • C. Washington
    Washington is a small town in Dutchess County, New York, known for its rural character and the village of Millbrook within its borders.
  • D. Washington
    Washington is a small rural town in Berkshire County in western Massachusetts, known for its forested landscape and quiet, sparsely populated character.
  • E. Washington
    Washington is a rapid transit station on Chicago's 'L' system, formerly serving the CTA Blue Line in the downtown Loop.
  • 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_69bd440b965081908b0557721cae6338 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6d7a42f88190bb1ef7261bcbc2a8 completed March 20, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69be67e0d88881909e378e919daab4e6 completed March 21, 2026, 9:41 a.m.
Created at: March 20, 2026, 1:26 p.m.