Triple
T14434809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yingkou Port |
E357931
|
entity |
| Predicate | nearCity |
P350
|
FINISHED |
| Object | Yingkou City |
E303634
|
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: Yingkou City | Statement: [Yingkou Port, nearCity, Yingkou City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yingkou City Context triple: [Yingkou Port, nearCity, Yingkou City]
-
A.
Yingkou
chosen
Yingkou is a coastal port city in northeastern China’s Liaoning Province, known as an important industrial and shipping hub on the Bohai Sea.
-
B.
Panjin
Panjin is an industrial and oil-producing city in northeastern China, best known for its striking Red Beach wetlands along the Bohai Sea.
-
C.
Jinzhou
Jinzhou is a prefecture-level port city in southwestern Liaoning Province, northeastern China, known for its industrial base and coastal location on the Bohai Sea.
-
D.
Liaoyuan
Liaoyuan is a prefecture-level city in northeastern China known for its coal mining history and location in the central part of Jilin Province.
-
E.
Laohekou City
Laohekou City is a county-level city in northwestern Hubei Province, China, known as a regional transport and commercial hub under the administration of Xiangyang.
- 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_69d8279402a88190821ffa39ae15bccf |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9148cf4481909082cc91b2f76218 |
completed | April 14, 2026, 7:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6d84fd888190b05dcf9191bae337 |
completed | May 8, 2026, 4:58 a.m. |
Created at: April 10, 2026, 1:18 a.m.