Triple

T2816270
Position Surface form Disambiguated ID Type / Status
Subject Suquamish E54294 entity
Predicate associatedWith P37 FINISHED
Object City of Seattle E1640 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: City of Seattle | Statement: [Suquamish, associatedWith, City of Seattle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Seattle
Context triple: [Suquamish, associatedWith, City of Seattle]
  • A. Seattle
    Seattle is a major coastal city in the U.S. state of Washington, known for its tech industry, vibrant music and arts scene, and iconic landmarks like the Space Needle.
  • B. Royal City, Washington
    Royal City, Washington is a small agricultural town in central Washington State known for its orchards and farming-based economy.
  • C. Seattle, Washington, United States chosen
    Seattle, Washington, United States is a major Pacific Northwest city known for its tech industry, vibrant cultural scene, and iconic landmarks like the Space Needle.
  • D. Tukwila
    Tukwila is a suburban city just south of Seattle, Washington, known as a regional transportation and retail hub.
  • E. Tacoma, Washington
    Tacoma, Washington is a mid-sized port city in the Pacific Northwest known for its waterfront, industrial history, and vibrant arts and museum scene.
  • 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_69ab49de0af08190b3da69683be1e728 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde4ed4ac81909f1ec4a3f7869bc1 completed March 7, 2026, 8:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69b4f00fe39481908cee24dc57be2b3b completed March 14, 2026, 5:20 a.m.
Created at: March 6, 2026, 9:59 p.m.