Triple
T20030807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Bangka Regency |
E495118
|
entity |
| Predicate | seat |
P75
|
FINISHED |
| Object | Muntok |
—
|
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: Muntok | Statement: [West Bangka Regency, seat, Muntok]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Muntok Context triple: [West Bangka Regency, seat, Muntok]
-
A.
Muntok
chosen
Muntok is a coastal town on the western tip of Bangka Island in Indonesia, historically known as an important tin-mining and trading port.
-
B.
Kuluncak
Kuluncak is a rural district and town in eastern Turkey known for its location within Malatya Province and its predominantly agricultural character.
-
C.
Sawu
Sawu is an Austronesian language spoken primarily on Savu (Sawu) Island in eastern Indonesia.
-
D.
Mendanau
Mendanau is an island in Indonesia’s Bangka Belitung province, known for its coastal landscapes and role in the region’s maritime and fishing activities.
-
E.
Mount Wanggameti
Mount Wanggameti is the tallest mountain on the Indonesian island of Sumba, known for its forested slopes and biodiversity within protected conservation areas.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66291a00c8190b0b895909f32d623 |
completed | April 20, 2026, 5:29 p.m. |
Created at: April 11, 2026, 3:36 p.m.