Triple
T20271017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Belitung Regency |
E499091
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Manggar |
—
|
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: Manggar | Statement: [East Belitung Regency, capital, Manggar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Manggar Context triple: [East Belitung Regency, capital, Manggar]
-
A.
Manggar
chosen
Manggar is a coastal town on Belitung Island in Indonesia, known for its tin mining history and numerous traditional coffee shops.
-
B.
Manggala
Manggala was a Mongol prince of the 13th century, notable as one of the sons of the Yuan dynasty founder Kublai Khan.
-
C.
Maranunggo
Maranunggo is an alternative name for the Marranunggu, an Aboriginal Australian people traditionally associated with the Northern Territory.
-
D.
Nanggu
Nanggu is an Oceanic language spoken by a small community in the Solomon Islands, known for its distinct phonology and limited number of speakers.
-
E.
Mangseng
Mangseng is an Oceanic language spoken in parts of western Melanesia, belonging to the Western Oceanic branch of the Austronesian language family.
- 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e675dd7c58819095bbf4baeda04d6a |
completed | April 20, 2026, 6:52 p.m. |
Created at: April 11, 2026, 11:42 p.m.