Triple
T6505125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southeast Sulawesi |
E149987
|
entity |
| Predicate | hasIsland |
P970
|
FINISHED |
| Object |
Kaledupa
Kaledupa is an island in Indonesia’s Wakatobi archipelago, known for its traditional villages, mangrove forests, and rich surrounding coral reefs.
|
E600665
|
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: Kaledupa | Statement: [Southeast Sulawesi, hasIsland, Kaledupa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaledupa Context triple: [Southeast Sulawesi, hasIsland, Kaledupa]
-
A.
Palena
Palena is a small town and municipality in the Palena Province of Chile’s Los Lagos Region, known for its remote Andean landscapes and outdoor tourism.
-
B.
Gandangara
Gandangara are an Aboriginal Australian people of the Southern Highlands and surrounding regions of New South Wales, known for their distinct language and cultural traditions.
-
C.
Kundagannada
Kundagannada is a regional dialect of the Kannada language spoken primarily in the coastal districts of Karnataka, India.
-
D.
Kiloran
Kiloran is a small coastal settlement on the Scottish island of Colonsay, known for its scenic bay and sandy beach.
-
E.
Kallady
Kallady is a coastal village in eastern Sri Lanka known for its beaches, fishing community, and proximity to the town of Batticaloa.
- 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: Kaledupa Triple: [Southeast Sulawesi, hasIsland, Kaledupa]
Generated description
Kaledupa is an island in Indonesia’s Wakatobi archipelago, known for its traditional villages, mangrove forests, and rich surrounding coral reefs.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kaledupa Target entity description: Kaledupa is an island in Indonesia’s Wakatobi archipelago, known for its traditional villages, mangrove forests, and rich surrounding coral reefs.
-
A.
Palena
Palena is a small town and municipality in the Palena Province of Chile’s Los Lagos Region, known for its remote Andean landscapes and outdoor tourism.
-
B.
Gandangara
Gandangara are an Aboriginal Australian people of the Southern Highlands and surrounding regions of New South Wales, known for their distinct language and cultural traditions.
-
C.
Kundagannada
Kundagannada is a regional dialect of the Kannada language spoken primarily in the coastal districts of Karnataka, India.
-
D.
Kiloran
Kiloran is a small coastal settlement on the Scottish island of Colonsay, known for its scenic bay and sandy beach.
-
E.
Kallady
Kallady is a coastal village in eastern Sri Lanka known for its beaches, fishing community, and proximity to the town of Batticaloa.
- 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_69c687ef291081909d437f035eef1cda |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c69966ff708190902c88cb6b48e5d7 |
completed | March 27, 2026, 2:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cb43db608190b785e77f6850bb6f |
completed | March 27, 2026, 6:24 p.m. |
| NEDg | Description generation | batch_69c6cc96edd08190b0c0f1b49dd64160 |
completed | March 27, 2026, 6:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6cd8d15ec8190be5a8c5e3f201139 |
completed | March 27, 2026, 6:33 p.m. |
Created at: March 27, 2026, 1:43 p.m.