Triple
T22543940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Makapuʻu Point |
E557366
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Sandy 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: Sandy Beach | Statement: [Makapuʻu Point, near, Sandy Beach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sandy Beach Context triple: [Makapuʻu Point, near, Sandy Beach]
-
A.
Sandy Beach
Sandy Beach is a popular surf and sunbathing beach in Rincón, Puerto Rico, known for its consistent waves, laid-back atmosphere, and scenic Caribbean coastline.
-
B.
Sandy Beach
chosen
Sandy Beach is a popular but notoriously powerful surf and bodysurfing beach on the southeastern shore of Oʻahu, Hawaii.
-
C.
Sandy Beach
Sandy Beach is a small public shoreline area in Cohasset, Massachusetts, known for its sandy waterfront and coastal recreation.
-
D.
Sandy Beach
Sandy Beach is a popular stretch of white sand and calm Caribbean waters in Saint Lucia’s Vieux Fort District, known for swimming, kitesurfing, and scenic coastal views.
-
E.
Sands Beach
Sands Beach is a popular waterfront recreation area in Port Royal, South Carolina, known for its sandy shoreline, fishing pier, and scenic views along the Beaufort River.
- 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_69e11e58662081909ae346ab384514ca |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f33c9cc819086d098f36e4121dc |
completed | April 29, 2026, 1:30 a.m. |
Created at: April 16, 2026, 8:51 p.m.