Triple
T15396165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banjar people |
E368181
|
entity |
| Predicate | alsoFoundIn |
P9687
|
FINISHED |
| Object | Brunei |
E11482
|
NE FINISHED |
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: Brunei | Statement: [Banjar people, alsoFoundIn, Brunei]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brunei Context triple: [Banjar people, alsoFoundIn, Brunei]
-
A.
Brunei Darussalam
chosen
Brunei Darussalam is a small, wealthy sultanate on the island of Borneo in Southeast Asia, known for its vast oil and gas reserves and absolute monarchy.
-
B.
Brunei-Kedayan
Brunei-Kedayan is a Malayic language variety spoken primarily by the Kedayan ethnic group in Brunei and surrounding regions of Borneo.
-
C.
Malaysia
Malaysia is a Southeast Asian country on the Malay Peninsula and parts of Borneo, known for its multicultural society, tropical rainforests, and rapidly developing economy.
-
D.
Malesia
Malesia is a biogeographical region in Southeast Asia encompassing the Malay Peninsula, Indonesia, the Philippines, New Guinea, and surrounding areas, known for its exceptionally rich tropical biodiversity.
-
E.
Waigani
Waigani is a suburb of Port Moresby in Papua New Guinea that serves as a key administrative and governmental center.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e8ac79081908ac79c0b3e7587ff |
completed | April 16, 2026, 1:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff133f242c819099ec5288ae4a622f |
completed | May 9, 2026, 10:58 a.m. |
Created at: April 10, 2026, 3:19 a.m.