Triple
T11394664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nusa Penida |
E269940
|
entity |
| Predicate | hasDiveSite |
P41537
|
FINISHED |
| Object |
Sental
Sental is a popular dive site off the coast of Nusa Penida, Indonesia, known for its clear waters, healthy coral reefs, and frequent sightings of pelagic marine life.
|
E923276
|
NE FINISHED |
How this triple was built (4 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: Sental | Statement: [Nusa Penida, hasDiveSite, Sental]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sental Context triple: [Nusa Penida, hasDiveSite, Sental]
-
A.
Sulien
Sulien is a Welsh saint traditionally venerated as a local holy figure associated with churches in Wales.
-
B.
Soral
Soral is a small rural municipality in southwestern Switzerland, located in the canton of Geneva near the French border.
-
C.
Sprantal
Sprantal is a village district of the town of Bretten in the state of Baden-Württemberg, Germany.
-
D.
Sikma
Sikma is a surname most notably associated with Jack Sikma, a Hall of Fame American basketball player known for his successful NBA career with the Seattle SuperSonics.
-
E.
Sosanya
Sosanya is a surname most notably associated with British actress Nina Sosanya, known for her extensive work in television, film, and theatre.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Sental Triple: [Nusa Penida, hasDiveSite, Sental]
Generated description
Sental is a popular dive site off the coast of Nusa Penida, Indonesia, known for its clear waters, healthy coral reefs, and frequent sightings of pelagic marine life.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sental Target entity description: Sental is a popular dive site off the coast of Nusa Penida, Indonesia, known for its clear waters, healthy coral reefs, and frequent sightings of pelagic marine life.
-
A.
Sulien
Sulien is a Welsh saint traditionally venerated as a local holy figure associated with churches in Wales.
-
B.
Soral
Soral is a small rural municipality in southwestern Switzerland, located in the canton of Geneva near the French border.
-
C.
Sprantal
Sprantal is a village district of the town of Bretten in the state of Baden-Württemberg, Germany.
-
D.
Sikma
Sikma is a surname most notably associated with Jack Sikma, a Hall of Fame American basketball player known for his successful NBA career with the Seattle SuperSonics.
-
E.
Sosanya
Sosanya is a surname most notably associated with British actress Nina Sosanya, known for her extensive work in television, film, and theatre.
- F. None of above. chosen
Provenance (5 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_69d6aacdbc6c8190af6dc3d5f5d22836 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d80018a58c81908b80dc9abd18d650 |
completed | April 9, 2026, 7:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e58cb43b988190876af2de4be49628 |
completed | April 20, 2026, 2:17 a.m. |
| NEDg | Description generation | batch_69e5932e23308190b1a8939ec2a60ec5 |
completed | April 20, 2026, 2:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e59a17de98819083b8de60d564cb83 |
completed | April 20, 2026, 3:14 a.m. |
Created at: April 8, 2026, 9:34 p.m.