Triple
T6890314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kayan |
E159027
|
entity |
| Predicate | associatedRiver |
P165
|
FINISHED |
| Object | Baram River |
E208163
|
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: Baram River | Statement: [Kayan, associatedRiver, Baram River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baram River Context triple: [Kayan, associatedRiver, Baram River]
-
A.
Baram River
chosen
The Baram River is one of the largest rivers in northern Borneo, flowing through the Malaysian state of Sarawak to the South China Sea and supporting diverse indigenous communities and rainforest ecosystems.
-
B.
Nakdong River
The Nakdong River is South Korea's longest river, flowing through the southeastern region and playing a crucial role in the country's history, ecology, and economy.
-
C.
Namgang River
The Namgang River is a scenic waterway in South Korea known for flowing through Jinju and hosting the famous Jinju Namgang Yudeung (Lantern) Festival.
-
D.
Neryungri River
Neryungri River is a river in the Sakha Republic (Yakutia), Russia, that gives its name to the nearby mining town of Neryungri.
-
E.
Yeong River
The Yeong River is a river in South Korea that feeds into the larger Nakdong River system.
- 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_69c6883568c8819081db6407e892cccc |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d92d45f08190a730b3842c95b521 |
completed | March 27, 2026, 7:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c769f2269c8190a476287a8ad4bec9 |
completed | March 28, 2026, 5:41 a.m. |
Created at: March 27, 2026, 2:23 p.m.