Triple
T18177985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Beach TV |
E435211
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Big 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: Big Beach | Statement: [Big Beach TV, partOf, Big Beach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Big Beach Context triple: [Big Beach TV, partOf, Big Beach]
-
A.
Big Beach
Big Beach is a famous wide, golden-sand beach in Makena, Maui, known for its powerful shore break and scenic views.
-
B.
Big Beach
chosen
Big Beach is an independent film production company known for producing acclaimed character-driven movies such as "Little Miss Sunshine" and "The Farewell."
-
C.
Wild Beach
Wild Beach is a scenic coastal area associated with Amala, known for its natural, undeveloped shoreline and tranquil seaside atmosphere.
-
D.
Summerland Beach
Summerland Beach is a popular coastal spot on Phillip Island in Victoria, Australia, best known for its scenic shoreline and nearby penguin viewing attractions.
-
E.
An Bang Beach
An Bang Beach is a popular white-sand coastal destination in central Vietnam known for its relaxed atmosphere, seafood restaurants, and proximity to the historic town of Hoi An.
- 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_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4df5b68f081908aac8210270f1499 |
completed | April 19, 2026, 1:57 p.m. |
Created at: April 10, 2026, 10:31 a.m.