Triple
T12868102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Wangwu |
E307772
|
entity |
| Predicate | nearRiver |
P350
|
FINISHED |
| Object | Yellow River |
E16374
|
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: Yellow River | Statement: [Mount Wangwu, nearRiver, Yellow River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yellow River Context triple: [Mount Wangwu, nearRiver, Yellow River]
-
A.
Yellow River
chosen
The Yellow River is the second-longest river in China, historically known as the cradle of Chinese civilization and notorious for its devastating floods and heavy silt load.
-
B.
Yellow River
The Yellow River is a river in the U.S. state of Florida that flows through the western Panhandle before emptying into Escambia Bay near the Gulf of Mexico.
-
C.
Yellow River
The Yellow River is a tributary stream that feeds into Lough Allen, a lake in the River Shannon system in Ireland.
-
D.
Hwang River
The Hwang River is a river in South Korea that feeds into the Nakdong River, contributing to one of the country’s major watershed systems.
-
E.
Chang River
The Chang River is a significant waterway flowing through Jingdezhen, a city in Jiangxi Province renowned for its porcelain production.
- 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9708f510c8190b4c64dc340420e85 |
completed | April 10, 2026, 9:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69b88d7048190bb584aa48bba5288 |
completed | May 3, 2026, 12:49 a.m. |
Created at: April 9, 2026, 5:38 p.m.