Triple
T12285153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sea Breeze |
E292809
|
entity |
| Predicate | isSimilarTo |
P278
|
FINISHED |
| Object | Bay Breeze |
E292809
|
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: Bay Breeze | Statement: [Sea Breeze, isSimilarTo, Bay Breeze]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bay Breeze Context triple: [Sea Breeze, isSimilarTo, Bay Breeze]
-
A.
Sea Breeze
chosen
Sea Breeze is a classic vodka-based cocktail typically made with cranberry and grapefruit juices, known for its light, refreshing taste.
-
B.
Seabreeze
Seabreeze was a former neighboring city to Daytona Beach, Florida, that was eventually incorporated into the larger Daytona Beach municipality.
-
C.
Cool Breeze
Cool Breeze is an American rapper from Atlanta best known as a member of the Dungeon Family collective alongside acts like Outkast and Goodie Mob.
-
D.
Breeze
Breeze is a web conferencing and e-learning software platform originally developed by Macromedia for online presentations, training, and collaboration.
-
E.
Tropical Breeze
"Tropical Breeze" is a video and installation artwork by contemporary artist Mika Rottenberg that explores themes of labor, globalization, and the absurd through surreal, factory-like scenarios.
- 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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91d1ede3081908647595739c3e996 |
completed | April 10, 2026, 3:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e7315608190963c714a0b128dbb |
completed | May 2, 2026, 3:55 p.m. |
Created at: April 8, 2026, 9:52 p.m.