Triple

T16138173
Position Surface form Disambiguated ID Type / Status
Subject United States E391584 entity
Predicate hasPart P35 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: [United States, hasPart, Washington]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Washington
Context triple: [United States, hasPart, 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 small town in Dutchess County, New York, known for its rural character and the village of Millbrook within its borders.
  • C. Washington
    Washington is a small rural town in Berkshire County in western Massachusetts, known for its forested landscape and quiet, sparsely populated character.
  • D. Washington
    Washington is the given first name of Uruguayan former professional footballer and coach Sebastián "Loco" Abreu.
  • E. Washington
    Washington is the capital city of the United States, known as the center of the federal government and home to numerous national monuments and institutions.
  • 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_69d87f1bb0988190b490d273dbf3fd03 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21a05e68881908319454a478cdda5 completed April 17, 2026, 11:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff29836bc8190b35f528d3e8547be completed May 10, 2026, 2:51 a.m.
Created at: April 10, 2026, 5:01 a.m.