Triple
T12620819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dandong |
E301373
|
entity |
| Predicate | hasCountyLevelCity |
P27799
|
FINISHED |
| Object |
Donggang
Donggang is a county-level coastal city in southeastern Liaoning Province, China, known for its fishing industry and proximity to the North Korean border.
|
E992841
|
NE FINISHED |
How this triple was built (4 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: [Dandong, hasCountyLevelCity, Donggang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Donggang Context triple: [Dandong, hasCountyLevelCity, Donggang]
-
A.
Sokcho
Sokcho is a coastal city in northeastern South Korea known for its beaches, seafood, and proximity to Seoraksan National Park.
-
B.
Tangqiao
Tangqiao is a Shanghai Metro station located in the city's central area, serving passengers on the circular Line 4 route.
-
C.
Donggang District
Donggang District is the central urban district and administrative seat of the coastal city of Rizhao in Shandong Province, China.
-
D.
Yanbian
Yanbian is an autonomous prefecture in northeastern China's Jilin Province, known for its significant ethnic Korean population and cultural ties to the Korean Peninsula.
-
E.
Gwangyang
Gwangyang is an industrial port city in South Korea known for its major steelworks complex and scenic coastal and mountainous landscapes.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Donggang Triple: [Dandong, hasCountyLevelCity, Donggang]
Generated description
Donggang is a county-level coastal city in southeastern Liaoning Province, China, known for its fishing industry and proximity to the North Korean border.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Donggang Target entity description: Donggang is a county-level coastal city in southeastern Liaoning Province, China, known for its fishing industry and proximity to the North Korean border.
-
A.
Sokcho
Sokcho is a coastal city in northeastern South Korea known for its beaches, seafood, and proximity to Seoraksan National Park.
-
B.
Tangqiao
Tangqiao is a Shanghai Metro station located in the city's central area, serving passengers on the circular Line 4 route.
-
C.
Donggang District
Donggang District is the central urban district and administrative seat of the coastal city of Rizhao in Shandong Province, China.
-
D.
Yanbian
Yanbian is an autonomous prefecture in northeastern China's Jilin Province, known for its significant ethnic Korean population and cultural ties to the Korean Peninsula.
-
E.
Gwangyang
Gwangyang is an industrial port city in South Korea known for its major steelworks complex and scenic coastal and mountainous landscapes.
- F. None of above. chosen
Provenance (5 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_69d7bdeaf49c8190b13800111fa77ea3 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d960c75c9c819092265ebc2b39f21d |
completed | April 10, 2026, 8:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ed6f79881908872c644a9789f04 |
completed | May 2, 2026, 8:30 p.m. |
| NEDg | Description generation | batch_69f660294004819089714099a08085f6 |
completed | May 2, 2026, 8:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6613ce1108190851cf8491fe666c8 |
completed | May 2, 2026, 8:40 p.m. |
Created at: April 9, 2026, 5:13 p.m.