Triple
T4268765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Batumi Boulevard |
E96887
|
entity |
| Predicate | hasView |
P854
|
FINISHED |
| Object | Batumi beach |
E41677
|
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: Batumi beach | Statement: [Batumi Boulevard, hasView, Batumi beach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Batumi beach Context triple: [Batumi Boulevard, hasView, Batumi beach]
-
A.
White Beach
White Beach is a small coastal beach in the town of Manchester-by-the-Sea, Massachusetts, known for its scenic shoreline and tranquil atmosphere.
-
B.
Batumi Sea Port
Batumi Sea Port is a major Black Sea maritime hub in Georgia, serving as a key gateway for regional trade and transportation.
-
C.
Batumi
chosen
Batumi is a major Black Sea resort city in southwestern Georgia known for its beaches, modern skyline, and role as a regional economic and cultural hub.
-
D.
Borsh Beach
Borsh Beach is a long, pebbly seaside destination on Albania’s Ionian coast, known for its clear turquoise waters and relatively unspoiled, laid-back atmosphere.
-
E.
Riva-Bella beach
Riva-Bella beach is a popular Normandy seaside beach in northern France, known for its wide sandy shoreline and role in the D-Day landings during World War II.
- 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_69b34543f06c8190915ebb1a4574ffa9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34ff913608190b6ccf4a85057b07b |
completed | March 12, 2026, 11:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5c71c9b488190abbca16d3ea70ae8 |
completed | March 14, 2026, 8:37 p.m. |
Created at: March 12, 2026, 11:07 p.m.