Triple

T1200833
Position Surface form Disambiguated ID Type / Status
Subject Susan Silver E25776 entity
Predicate residence P75 FINISHED
Object Seattle E166067 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: Seattle | Statement: [Susan Silver, residence, Seattle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seattle
Context triple: [Susan Silver, residence, Seattle]
  • A. Seattle chosen
    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. Tukwila
    Tukwila is a suburban city just south of Seattle, Washington, known as a regional transportation and retail hub.
  • C. Portland
    Portland is the largest city in Oregon, known for its vibrant arts scene, progressive culture, and lush green spaces in the Pacific Northwest.
  • D. Portland
    Portland is the largest city in the U.S. state of Maine, known for its historic waterfront, vibrant arts scene, and coastal New England charm.
  • E. Portland
    Portland is a small historic town in the Central Tablelands region of New South Wales, Australia, known for its early cement works and heritage streetscapes.
  • 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_69a49429f5ec8190a6a205eb0ae81e5e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd9ec3488190afe35af54efae5e9 completed March 1, 2026, 10:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae890a2a0c8190a83cda5f037763bd completed March 9, 2026, 8:47 a.m.
Created at: March 1, 2026, 7:46 p.m.