Triple
T5647636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colusa County |
E124422
|
entity |
| Predicate | countySeat |
P383
|
FINISHED |
| Object | Colusa |
E236824
|
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: Colusa | Statement: [Colusa County, countySeat, Colusa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Colusa Context triple: [Colusa County, countySeat, Colusa]
-
A.
Colusa
chosen
Colusa is a small agricultural city in California’s Sacramento Valley, known for its historic downtown and proximity to the Sacramento River.
-
B.
Menifee
Menifee is a rapidly growing suburban city in Southern California known for its residential communities and proximity to major Inland Empire urban centers.
-
C.
Yakima
Yakima is a city in south-central Washington State known as a major agricultural hub, particularly for apples, hops, and wine grapes.
-
D.
Oroville
Oroville is a small city in Northern California known for its proximity to the Oroville Dam and Lake Oroville recreation area.
-
E.
Creston
Creston is a small rural community in California known for its ranching heritage and proximity to the wine-producing regions of San Luis Obispo County.
- 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_69c00825df388190a58742fa9b1aa33d |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c022d1534c8190ac4828e44300fb91 |
completed | March 22, 2026, 5:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04d88bbf08190b32d1ad157e28fe4 |
completed | March 22, 2026, 8:14 p.m. |
Created at: March 22, 2026, 3:42 p.m.