Triple

T15508313
Position Surface form Disambiguated ID Type / Status
Subject Georgia (1995 film) E379138 entity
Predicate filmingLocation P40 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: [Georgia (1995 film), filmingLocation, Seattle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seattle
Context triple: [Georgia (1995 film), filmingLocation, 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. Bellevue, Washington
    Bellevue, Washington is a rapidly growing city in the Seattle metropolitan area known for its thriving tech industry, upscale downtown, and high quality of life.
  • D. Portland
    Portland is the largest city in Oregon, known for its vibrant arts scene, progressive culture, and lush green spaces in the Pacific Northwest.
  • E. 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.
  • 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03fcea8888190a7b69aca360183c3 completed April 16, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff453e3d3081909f6b6e8b67a824ac completed May 9, 2026, 2:31 p.m.
Created at: April 10, 2026, 3:55 a.m.