Triple

T1642501
Position Surface form Disambiguated ID Type / Status
Subject Hillsboro E35503 entity
Predicate hasIndustryCluster P759 FINISHED
Object Silicon Forest E30894 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: Silicon Forest | Statement: [Hillsboro, hasIndustryCluster, Silicon Forest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Silicon Forest
Context triple: [Hillsboro, hasIndustryCluster, Silicon Forest]
  • A. Silicon Forest chosen
    Silicon Forest is a high-tech industry region in and around Portland, Oregon, known for its concentration of electronics, semiconductor, and technology companies.
  • B. Silicon Valley
    Silicon Valley is a globally renowned technology and innovation hub in Northern California, home to many of the world’s leading tech companies and startups.
  • C. Silicon Valley of the North
    "Silicon Valley of the North" is a nickname for Waterloo, Ontario, highlighting its status as a major Canadian hub for technology companies, startups, and innovation.
  • D. Mountain View
    Mountain View is a Silicon Valley city in Northern California best known as a major technology hub and the home of companies like Google.
  • E. Cupertino
    Cupertino is a city in California best known as the longtime headquarters of Apple Inc. and a key hub of the global technology industry.
  • 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_69a88604618c81908b41f6429c431eb6 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90a3f4d8c8190aa0a44d1c9b1a7f0 completed March 5, 2026, 4:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad60a0096c81909dc723d0db95481e completed March 8, 2026, 11:42 a.m.
Created at: March 4, 2026, 7:28 p.m.