Triple
T16461372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mountain Winery |
E399813
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Saratoga |
E93326
|
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: Saratoga | Statement: [Mountain Winery, city, Saratoga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saratoga Context triple: [Mountain Winery, city, Saratoga]
-
A.
Saratoga
chosen
Saratoga is an affluent suburban city in California’s Silicon Valley, known for its upscale residential neighborhoods, wineries, and highly ranked schools.
-
B.
Saratoga
Saratoga is a coastal suburb on the Central Coast of New South Wales, Australia, known for its waterfront setting on Brisbane Water.
-
C.
Saratoga Battlefield
Saratoga Battlefield is a historic Revolutionary War site in upstate New York where American forces won a decisive victory over the British in 1777.
-
D.
Belmont Park
Belmont Park is a historic thoroughbred horse racing track on Long Island best known for hosting the Belmont Stakes, the final leg of the U.S. Triple Crown.
-
E.
Belmont Park
Belmont Park is a historic oceanfront amusement park in San Diego known for its classic wooden roller coaster, beachfront rides, and boardwalk attractions.
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32d819d548190bc76a0ec2e223437 |
completed | April 18, 2026, 7:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00581a11e881908681f68c26ee6a05 |
completed | May 10, 2026, 10:04 a.m. |
Created at: April 10, 2026, 5:10 a.m.