Triple
T13150769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mid-Columbia region |
E312458
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Hermiston |
E426916
|
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: Hermiston | Statement: [Mid-Columbia region, hasCity, Hermiston]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hermiston Context triple: [Mid-Columbia region, hasCity, Hermiston]
-
A.
Hermiston, Oregon
chosen
Hermiston, Oregon is a small city in northeastern Oregon known as an agricultural and transportation hub in the Columbia Basin.
-
B.
Isleton
Isleton is a small historic city in California’s Sacramento–San Joaquin River Delta, known for its legacy as a former riverboat and agricultural hub with notable Chinese and Japanese American heritage.
-
C.
Cottonwood Heights
Cottonwood Heights is a suburban city in northern Utah known for its proximity to the Wasatch Mountains and popular ski resorts.
-
D.
Hillsboro
Hillsboro is a small rural town in Pocahontas County, West Virginia, known for its scenic Appalachian setting and historic character.
-
E.
Hillsboro
Hillsboro is a major city in the Portland metropolitan area known as a hub of Oregon’s high-tech industry, often referred to as part of the “Silicon Forest.”
- 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_69d806aabde48190899e13e41659cae5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98bd1fc408190b4b5ca973bcee403 |
completed | April 10, 2026, 11:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6eaea3f888190b47ed7bf1c52e7e7 |
completed | May 3, 2026, 6:27 a.m. |
Created at: April 9, 2026, 9:11 p.m.