Triple
T14033366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hsinchu Air Base |
E337646
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Hsinchu |
E198701
|
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: Hsinchu | Statement: [Hsinchu Air Base, serves, Hsinchu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hsinchu Context triple: [Hsinchu Air Base, serves, Hsinchu]
-
A.
Hsinchu, Taiwan
chosen
Hsinchu, Taiwan is a major high-tech city often called Taiwan’s “Silicon Valley,” known for its science park and concentration of semiconductor and electronics companies.
-
B.
Taichung
Taichung is a major city in central Taiwan known for its cultural attractions, mild climate, and role as an important economic and transportation hub.
-
C.
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.
-
D.
Xinyi
Xinyi is a county-level city administered by Maoming in Guangdong Province, China, known for its agriculture and regional commerce.
-
E.
Xinyi
Xinyi is a county-level city administered by Xuzhou in Jiangsu Province, eastern China.
- 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_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2fac71188190a586049405f1071e |
completed | April 14, 2026, 12:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feef5c11708190a7fd4c0682b6ed81 |
completed | May 9, 2026, 8:25 a.m. |
Created at: April 9, 2026, 10:20 p.m.