Triple
T363372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Intel Ronler Acres Campus |
E7903
|
entity |
| Predicate | partOf |
P40
|
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: [Intel Ronler Acres Campus, partOf, Silicon Forest]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Silicon Forest Context triple: [Intel Ronler Acres Campus, partOf, 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.
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.
-
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.
Silicon Beach
Silicon Beach is a tech and startup hub along the coastal neighborhoods of Los Angeles, known for its concentration of technology companies, digital media firms, and entrepreneurial activity.
- 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_69a2ebd1016481909b8ba3b047a47145 |
completed | Feb. 28, 2026, 1:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3f4d8e8688190a35d50b99b85bb7f |
completed | March 1, 2026, 8:12 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.