Triple
T21191971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TD-SCDMA |
E522232
|
entity |
| Predicate | supportedBy |
P67
|
FINISHED |
| Object | China Mobile |
—
|
NE NERFINISHED |
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: China Mobile | Statement: [TD-SCDMA, supportedBy, China Mobile]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: China Mobile Context triple: [TD-SCDMA, supportedBy, China Mobile]
-
A.
China Mobile
chosen
China Mobile is a state-owned Chinese telecommunications company and one of the world’s largest mobile network operators by subscriber base.
-
B.
Unicom Corporation
Unicom Corporation was a major U.S. electric utility holding company based in Illinois that later became part of Exelon through a merger.
-
C.
Chunghwa Telecom
Chunghwa Telecom is Taiwan’s largest telecommunications company, providing a wide range of fixed-line, mobile, and broadband services.
-
D.
CMCC
CMCC is a public community college in Auburn, Maine, offering two-year degree and certificate programs across a range of academic and technical fields.
-
E.
Huawei
Huawei is a major Chinese multinational technology company best known globally for its telecommunications equipment, smartphones, and role in 5G network infrastructure.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69e0b51061388190aa03f19700d3ef04 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e733381f288190b3da795f62a39568 |
completed | April 21, 2026, 8:20 a.m. |
Created at: April 16, 2026, 3:07 p.m.