Triple
T8202330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 十堰 |
E191607
|
entity |
| Predicate | hasTouristAttraction |
P530
|
FINISHED |
| Object | 丹江口水库 |
E192640
|
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: 丹江口水库 | Statement: [十堰, hasTouristAttraction, 丹江口水库]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 丹江口水库 Context triple: [十堰, hasTouristAttraction, 丹江口水库]
-
A.
Danjiangkou
chosen
Danjiangkou is a county-level city in northwestern Hubei Province, China, known for the Danjiangkou Reservoir, a key source for the South–North Water Transfer Project.
-
B.
Meishan Reservoir
Meishan Reservoir is a major water storage and flood-control reservoir on China’s Huai River, supporting regional irrigation, water supply, and hydropower.
-
C.
汉江
汉江是中国长江中游最大的支流之一，流经陕西、湖北等地并在武汉与长江汇合。
-
D.
Liujiaxia Reservoir
Liujiaxia Reservoir is a large artificial lake on the Yellow River in north-central China, created by the Liujiaxia Dam and known for its hydroelectric power generation and scenic surroundings.
-
E.
Xin’anjiang Reservoir
Xin’anjiang Reservoir is a large artificial lake in eastern China, best known for its role in flood control, hydroelectric power generation, and the creation of the scenic Thousand Island Lake.
- 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_69ca82c7f3e08190857bf1fc63b2a10c |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb5df84b108190b4407a72a3500af9 |
completed | March 31, 2026, 5:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccedc49ba4819099762f200c4e6577 |
completed | April 1, 2026, 10:04 a.m. |
Created at: March 30, 2026, 5:43 p.m.