Triple
T21197451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cua Viet River |
E522362
|
entity |
| Predicate | nearbySettlement |
P350
|
FINISHED |
| Object | Dong Ha |
—
|
NE NERFINISHED |
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: Dong Ha | Statement: [Cua Viet River, nearbySettlement, Dong Ha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dong Ha Context triple: [Cua Viet River, nearbySettlement, Dong Ha]
-
A.
Dong Ha
chosen
Dong Ha is a city in central Vietnam that serves as the administrative, economic, and transportation hub of Quang Tri Province.
-
B.
Wang Jeon
Wang Jeon, better known by his temple name Emperor Gongmin, was a 14th-century king of Korea’s Goryeo dynasty noted for efforts to reform government and resist Mongol influence.
-
C.
Chung-ho
Chung-ho is the former romanized name of Zhonghe District, a populous urban district in New Taipei City, Taiwan.
-
D.
Tae-ho
Tae-ho is the resourceful yet troubled space scavenger protagonist of the South Korean sci-fi film "Space Sweepers."
-
E.
Jeong Hyeong-don
Jeong Hyeong-don is a South Korean comedian and television host best known for his work on popular variety shows such as "Infinite Challenge" and "Weekly Idol."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b51061388190aa03f19700d3ef04 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7333c9bac8190a203802a8b8e4143 |
completed | April 21, 2026, 8:20 a.m. |
Created at: April 16, 2026, 3:11 p.m.