Triple
T17477606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phú Yên province |
E425578
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Đông Hòa town |
—
|
NE NERFINISHED |
How this triple was built (3 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: Đông Hòa town | Statement: [Phú Yên province, contains, Đông Hòa town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Đông Hòa town Context triple: [Phú Yên province, contains, Đông Hòa town]
-
A.
Donghe Township
Donghe Township is a rural coastal township in eastern Taiwan known for its scenic Pacific shoreline, hot springs, and surfing beaches.
-
B.
Miaohang Town
Miaohang Town is a suburban township-level division in the northern part of Shanghai, China, known for its mix of residential, industrial, and developing urban areas.
-
C.
Jinhu Township
Jinhu Township is a rural coastal township in Kinmen County, Taiwan, known for its military history, traditional villages, and role as a frontline outpost near mainland China.
-
D.
Huanghua Town
Huanghua Town is a township-level division in the Changsha area of Hunan Province, China, known primarily for encompassing the vicinity of Changsha Huanghua International Airport.
-
E.
Zhushan Town
Zhushan Town is the main urban and political hub of Zhushan County in Hubei Province, China, serving as its central seat of local government and administration.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Đông Hòa town Target entity description: Đông Hòa town is a coastal urban district-level town in south-central Vietnam known for its location along the East Sea and its role in the economy of Phú Yên province.
-
A.
Donghe Township
Donghe Township is a rural coastal township in eastern Taiwan known for its scenic Pacific shoreline, hot springs, and surfing beaches.
-
B.
Miaohang Town
Miaohang Town is a suburban township-level division in the northern part of Shanghai, China, known for its mix of residential, industrial, and developing urban areas.
-
C.
Jinhu Township
Jinhu Township is a rural coastal township in Kinmen County, Taiwan, known for its military history, traditional villages, and role as a frontline outpost near mainland China.
-
D.
Huanghua Town
Huanghua Town is a township-level division in the Changsha area of Hunan Province, China, known primarily for encompassing the vicinity of Changsha Huanghua International Airport.
-
E.
Zhushan Town
Zhushan Town is the main urban and political hub of Zhushan County in Hubei Province, China, serving as its central seat of local government and administration.
- F. None of above. chosen
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_69d889dbc2e88190b18ea6115e819258 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451bd865081909b5f84405c40ff14 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 5:47 a.m.