Triple
T7201811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tao River |
E168763
|
entity |
| Predicate | nameInEnglish |
P3437
|
FINISHED |
| Object | Tao River |
E168763
|
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: Tao River | Statement: [Tao River, nameInEnglish, Tao River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tao River Context triple: [Tao River, nameInEnglish, Tao River]
-
A.
Tao River
chosen
The Tao River is a significant tributary in northwestern China that flows through Gansu Province before joining the Yellow River.
-
B.
Tyya River
The Tyya River is a tributary watercourse in Siberia that feeds into Russia’s Lake Baikal, the world’s deepest and oldest freshwater lake.
-
C.
Tayura River
The Tayura River is a Siberian watercourse in Russia that serves as a tributary within the Lena River basin, contributing to the region’s extensive river network.
-
D.
Ariguanabo River
The Ariguanabo River is a waterway in western Cuba that flows through the town of San Antonio de los Baños in Artemisa Province.
-
E.
Yodo River
The Yodo River is a major waterway in Japan’s Kansai region that flows through Kyoto and Osaka, historically serving as an important route for transport, trade, and urban development.
- 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_69c68a5376748190bb500f03df86e93e |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6e94971508190bb38184c9af2fe51 |
completed | March 27, 2026, 8:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf4205d7a08190839c10bdfc476d9f |
completed | April 3, 2026, 4:28 a.m. |
Created at: March 27, 2026, 2:52 p.m.