Triple
T12666643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fuxing series EMU |
E302568
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Fuxing Hao |
E923682
|
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: Fuxing Hao | Statement: [Fuxing series EMU, alsoKnownAs, Fuxing Hao]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fuxing Hao Context triple: [Fuxing series EMU, alsoKnownAs, Fuxing Hao]
-
A.
Fuxing
chosen
Fuxing is a series of Chinese high-speed electric multiple unit trains known for their advanced technology, high operating speeds, and use on major routes across China’s high-speed rail network.
-
B.
Yongqi
Yongqi was a Qing dynasty imperial prince, noted as one of the most talented sons of the Qianlong Emperor before his early death.
-
C.
Dongfeng
Dongfeng is a major Chinese state-owned automobile manufacturer known for producing a wide range of commercial and passenger vehicles and partnering with global car brands.
-
D.
Jiangling
Jiangling was an important ancient Chinese city that served as a major political and cultural center of the State of Chu during the Zhou dynasty period.
-
E.
Zhongxiao Fuxing
Zhongxiao Fuxing is a key Taipei Metro station in central Taipei that serves as a busy transfer hub between multiple subway lines and a gateway to nearby commercial and shopping districts.
- 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96181c40481908f3e2717f5472b85 |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6688a19148190b8d252d3706d2b05 |
completed | May 2, 2026, 9:11 p.m. |
Created at: April 9, 2026, 5:19 p.m.