Triple
T6148732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Taiwan |
E137143
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Pingtung City |
E570111
|
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: Pingtung City | Statement: [Southern Taiwan, hasMajorCity, Pingtung City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pingtung City Context triple: [Southern Taiwan, hasMajorCity, Pingtung City]
-
A.
Pingtung City
chosen
Pingtung City is an urban center in southern Taiwan known as the political and economic hub of Pingtung County.
-
B.
Tainan
Tainan is a historic city in southern Taiwan known for its well-preserved temples, traditional culture, and status as the island’s former capital.
-
C.
Ping-tung County
Ping-tung County is a largely rural county at the southern tip of Taiwan, known for its tropical climate, coastal scenery, and attractions such as Kenting National Park.
-
D.
Xinyi
Xinyi is a county-level city administered by Xuzhou in Jiangsu Province, eastern China.
-
E.
Kaohsiung
Kaohsiung is a major port city in southern Taiwan known for its heavy industry, modern harborfront, and growing cultural and arts scene.
- 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_69c008a2c6308190a56519b22d55d083 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05ce21820819096be9159d6b70a5f |
completed | March 22, 2026, 9:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5e3cbf914819086c9553904aee0e5 |
completed | March 27, 2026, 1:56 a.m. |
Created at: March 22, 2026, 4:16 p.m.