Triple
T19508107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Washington Coast |
E488078
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Shi Shi Beach |
—
|
NE NERFINISHED |
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: Shi Shi Beach | Statement: [Washington Coast, contains, Shi Shi Beach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shi Shi Beach Context triple: [Washington Coast, contains, Shi Shi Beach]
-
A.
Shi Shi Beach
chosen
Shi Shi Beach is a remote, rugged coastal beach on Washington State’s Olympic Peninsula, renowned for its dramatic sea stacks, tide pools, and scenic hiking access.
-
B.
Samae Beach
Samae Beach is a popular sandy shoreline on the island of Koh Larn in Thailand, known for its clear waters, water sports, and relaxed resort atmosphere.
-
C.
Shilaoren Beach
Shilaoren Beach is a popular coastal tourist spot in Qingdao known for its sandy shoreline, scenic sea views, and recreational activities.
-
D.
Serasa Beach
Serasa Beach is a popular coastal recreation area in Brunei known for its sandy shoreline, water sports, and seaside leisure facilities.
-
E.
Laiya Beach
Laiya Beach is a popular white-sand beach destination in the Philippines known for its clear waters, resorts, and water activities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e635130e708190bb3d70e1abbade2a |
completed | April 20, 2026, 2:15 p.m. |
Created at: April 10, 2026, 1:40 p.m.