Triple

T364674
Position Surface form Disambiguated ID Type / Status
Subject Jobs (2013 film) E7931 entity
Predicate setIn P1393 FINISHED
Object Silicon Valley E441 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 Valley | Statement: [Jobs (2013 film), setIn, Silicon Valley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Silicon Valley
Context triple: [Jobs (2013 film), setIn, Silicon Valley]
  • A. Silicon Valley chosen
    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.
  • B. Silicon Forest
    Silicon Forest is a high-tech industry region in and around Portland, Oregon, known for its concentration of electronics, semiconductor, and technology companies.
  • C. Menlo Park, California
    Menlo Park, California is a city in Silicon Valley known as a hub for technology and venture capital, home to major research institutions and tech companies.
  • D. 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.
  • E. Palo Alto, California
    Palo Alto, California is a major Silicon Valley city known for its role as a global technology and innovation hub and as the home of Stanford University.
  • 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_69a2e7e880008190a6ad7e06e5d03007 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ebe6c1b4819083335e880c205ed6 completed Feb. 28, 2026, 1:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d6061508190b6fd3c907107fc63 completed March 3, 2026, 11:23 p.m.
Created at: Feb. 28, 2026, 1:08 p.m.