Triple
T7625118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nantan |
E172607
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object | Yura River |
E665324
|
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: Yura River | Statement: [Nantan, hasRiver, Yura River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yura River Context triple: [Nantan, hasRiver, Yura River]
-
A.
Yura River
chosen
The Yura River is a major river in the northern Kansai region of Japan, flowing through Kyoto and Hyōgo Prefectures before emptying into the Sea of Japan.
-
B.
Yana River
The Yana River is a major river in northeastern Siberia, Russia, that flows northward into the Laptev Sea of the Arctic Ocean.
-
C.
Kasplya River
The Kasplya River is a tributary waterway in Eastern Europe that feeds into the larger Daugava River system.
-
D.
Benya River
Benya River is a watercourse in Ghana’s Central Region that flows into the Gulf of Guinea and helps form the Benya Lagoon near the coastal town of Elmina.
-
E.
Lika River
The Lika River is a karst river in the Lika region of Croatia, known for its sinking course and role in feeding the Lika hydroelectric 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_69c699517e348190bd3348b6889200f2 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fa6648608190a9203b98b76209aa |
completed | March 27, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cde6a2bdd08190897705615109dae0 |
completed | April 2, 2026, 3:46 a.m. |
Created at: March 27, 2026, 3:56 p.m.