Triple
T15591009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liaoning coastal economic belt |
E374741
|
entity |
| Predicate | hasKeyCity |
P316
|
FINISHED |
| Object | Donggang |
E992841
|
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: Donggang | Statement: [Liaoning coastal economic belt, hasKeyCity, Donggang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Donggang Context triple: [Liaoning coastal economic belt, hasKeyCity, Donggang]
-
A.
Donggang
chosen
Donggang is a county-level coastal city in southeastern Liaoning Province, China, known for its fishing industry and proximity to the North Korean border.
-
B.
Shidao
Shidao is a small island in the South China Sea that forms part of the Amphitrite Group within the disputed Paracel Islands archipelago.
-
C.
Zhanshan
Zhanshan is a Chinese given name that can be borne by individuals such as Zhu Zhanshan.
-
D.
Sokcho
Sokcho is a coastal city in northeastern South Korea known for its beaches, seafood, and proximity to Seoraksan National Park.
-
E.
Tangqiao
Tangqiao is a Shanghai Metro station located in the city's central area, serving passengers on the circular Line 4 route.
- 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_69d85cce25008190b13b52745fbd719b |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e4b903c8190a35f9267cb38e721 |
completed | April 16, 2026, 2:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff56c5baac819099d53896f6a35d94 |
completed | May 9, 2026, 3:46 p.m. |
Created at: April 10, 2026, 4:11 a.m.