Triple
T3637710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Control Yuan |
E77111
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
Jiānchá Yuàn
Jiānchá Yuàn is the Chinese name for Taiwan’s Control Yuan, an independent government watchdog body responsible for monitoring public officials and investigating government misconduct.
|
E376148
|
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: Jiānchá Yuàn | Statement: [Control Yuan, alsoKnownAs, Jiānchá Yuàn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jiānchá Yuàn Context triple: [Control Yuan, alsoKnownAs, Jiānchá Yuàn]
-
A.
Zhenyuan
Zhenyuan was a late 19th-century Chinese ironclad battleship of the Beiyang Fleet that played a prominent role in the First Sino-Japanese War.
-
B.
Younan Xia
Younan Xia is a prominent chemist and materials scientist known for his pioneering work in nanomaterials synthesis and nanotechnology.
-
C.
Yu Xuezhong
Yu Xuezhong was a prominent Chinese military leader associated with the Northeastern Army during the Republican era.
-
D.
Jun Xia
Jun Xia is a Chinese architect best known for serving as the lead designer of Shanghai Tower, one of the world’s tallest skyscrapers.
-
E.
Yuanhong
Yuanhong is a Chinese given name that appears in the full name of the historical figure Li Yuanhong.
- 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: Jiānchá Yuàn Triple: [Control Yuan, alsoKnownAs, Jiānchá Yuàn]
Generated description
Jiānchá Yuàn is the Chinese name for Taiwan’s Control Yuan, an independent government watchdog body responsible for monitoring public officials and investigating government misconduct.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jiānchá Yuàn Target entity description: Jiānchá Yuàn is the Chinese name for Taiwan’s Control Yuan, an independent government watchdog body responsible for monitoring public officials and investigating government misconduct.
-
A.
Zhenyuan
Zhenyuan was a late 19th-century Chinese ironclad battleship of the Beiyang Fleet that played a prominent role in the First Sino-Japanese War.
-
B.
Younan Xia
Younan Xia is a prominent chemist and materials scientist known for his pioneering work in nanomaterials synthesis and nanotechnology.
-
C.
Yu Xuezhong
Yu Xuezhong was a prominent Chinese military leader associated with the Northeastern Army during the Republican era.
-
D.
Jun Xia
Jun Xia is a Chinese architect best known for serving as the lead designer of Shanghai Tower, one of the world’s tallest skyscrapers.
-
E.
Yuanhong
Yuanhong is a Chinese given name that appears in the full name of the historical figure Li Yuanhong.
- 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_69ad85dd0be48190b738990cb20c4731 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc328e5e481909d26318c743bc84a |
completed | March 8, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b44f23298481909d313d6b3f8013cd |
completed | March 13, 2026, 5:53 p.m. |
| NEDg | Description generation | batch_69b450785378819090b4ed7536db7757 |
completed | March 13, 2026, 5:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b45a0afef8819097c6e87127b4d1db |
completed | March 13, 2026, 6:40 p.m. |
Created at: March 8, 2026, 3:24 p.m.