Triple
T71674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chardonnay |
E1433
|
entity |
| Predicate | primaryRegion |
P1103
|
FINISHED |
| Object | Sonoma |
E16463
|
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: Sonoma | Statement: [Chardonnay, primaryRegion, Sonoma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sonoma Context triple: [Chardonnay, primaryRegion, Sonoma]
-
A.
Napa
Napa is a city in Northern California that serves as the commercial and cultural hub of the renowned Napa Valley wine region.
-
B.
Sonoma Valley
chosen
Sonoma Valley is a renowned wine-producing region in California celebrated for its vineyards, wineries, and scenic landscapes.
-
C.
Santa Rosa
Santa Rosa is a mid-sized city in Sonoma County known as a cultural and economic hub of California’s wine country.
-
D.
Calistoga
Calistoga is a small resort town in California’s Napa Valley known for its wineries, hot springs, and relaxed, historic charm.
-
E.
Napa Valley
Napa Valley is a renowned wine-producing region in Northern California, famous for its vineyards, wineries, and picturesque landscapes.
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24f0578808190be793d7a161c2cf5 |
completed | Feb. 28, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a34417410081909ea9d7c424224bc5 |
completed | Feb. 28, 2026, 7:37 p.m. |
Created at: Feb. 28, 2026, 2:03 a.m.