Triple
T12663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California quail |
E255
|
entity |
| Predicate | nativeTo |
P410
|
FINISHED |
| Object | Washington |
E20479
|
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: Washington | Statement: [California quail, nativeTo, Washington]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Washington Context triple: [California quail, nativeTo, Washington]
-
A.
Washington
chosen
Washington is a U.S. state in the Pacific Northwest known for its diverse landscapes, technology industry centered around Seattle, and significant cultural and economic influence on the West Coast.
-
B.
Oregon
Oregon is a U.S. state in the Pacific Northwest known for its diverse landscapes, including rugged coastline, dense forests, mountains, and high desert, as well as its environmentally conscious culture.
-
C.
Washington, D.C.
Washington, D.C. is the capital city of the United States, serving as the nation’s political center and home to its federal government institutions.
-
D.
Maryland
Maryland is a Mid-Atlantic U.S. state known for its Chesapeake Bay shoreline, colonial history, and proximity to the nation’s capital.
-
E.
Wisconsin
Wisconsin is a U.S. state in the Upper Midwest known for its dairy industry, Great Lakes shorelines, and mix of rural landscapes and industrial cities.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a2465b2cf881908bf61c461e04cf6a |
completed | Feb. 28, 2026, 1:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a34417410081909ea9d7c424224bc5 |
completed | Feb. 28, 2026, 7:37 p.m. |
Created at: Feb. 28, 2026, 1:02 a.m.