Triple
T2790652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ZTE |
E61920
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object | ZTE USA |
E61920
|
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: ZTE USA | Statement: [ZTE, hasSubsidiary, ZTE USA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ZTE USA Context triple: [ZTE, hasSubsidiary, ZTE USA]
-
A.
ZTE
chosen
ZTE is a major Chinese telecommunications and technology company known for manufacturing network equipment and smartphones and competing globally with firms like Nokia and Huawei.
-
B.
T-Mobile US
T-Mobile US is a major American wireless network operator known for its nationwide mobile phone services and aggressive “Un-carrier” marketing strategy.
-
C.
Huawei
Huawei is a major Chinese multinational technology company best known globally for its telecommunications equipment, smartphones, and role in 5G network infrastructure.
-
D.
Alcatel
Alcatel is a multinational telecommunications equipment and networking company known for providing infrastructure, mobile, and broadband solutions worldwide.
-
E.
Radisys
Radisys is a U.S.-based telecommunications solutions company known for providing open telecom and digital infrastructure platforms to service providers and network operators worldwide.
- 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_69ab4b7f51d881908768300ebd2fbdae |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddceb9d88190961e30d521a21552 |
completed | March 7, 2026, 8:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc65c1f848190b6efeefb64a3e131 |
completed | March 10, 2026, 7:21 a.m. |
Created at: March 6, 2026, 9:58 p.m.