Triple

T1909402
Position Surface form Disambiguated ID Type / Status
Subject LMN Architects E38074 entity
Predicate locationState P562 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: [LMN Architects, locationState, Washington]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Washington
Context triple: [LMN Architects, locationState, Washington]
  • A. Washington
    Washington is a small town in Dutchess County, New York, known for its rural character and the village of Millbrook within its borders.
  • B. 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.
  • C. Washington
    Washington is a common English surname most famously borne by George Washington, the first president of the United States.
  • 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. Oregon
    Oregon is a U.S. state in the Pacific Northwest known for its diverse landscapes, including rugged coastline, dense forests, mountains, and high desert, as well as its environmentally conscious culture.
  • 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_69a8862a26088190aae5243695aeefc0 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb1b7095c8190ad7e472aada30d3d completed March 7, 2026, 5:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae892409f4819094ee3acc6942d1ee completed March 9, 2026, 8:47 a.m.
Created at: March 4, 2026, 7:35 p.m.