Triple
T3419280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mi TV |
E72079
|
entity |
| Predicate | manufacturer |
P490
|
FINISHED |
| Object | Xiaomi |
E321474
|
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: Xiaomi | Statement: [Mi TV, manufacturer, Xiaomi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xiaomi Context triple: [Mi TV, manufacturer, Xiaomi]
-
A.
Xiaomi
chosen
Xiaomi is a major Chinese electronics and smartphone manufacturer known for its affordable, feature-rich devices and rapidly growing global presence.
-
B.
Huawei
Huawei is a major Chinese multinational technology company best known globally for its telecommunications equipment, smartphones, and role in 5G network infrastructure.
-
C.
HTC
HTC is a Taiwanese consumer electronics company best known for manufacturing smartphones and other mobile devices, including early Android and Windows-based phones.
-
D.
Sony Mobile Communications
Sony Mobile Communications is a former mobile phone division of Sony known for developing and marketing Xperia smartphones and related mobile devices.
-
E.
ZTE
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.
- 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_69ad85ad38e48190b7660c5118a35289 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb94d6808819080997df30119e71e |
completed | March 8, 2026, 6 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b354701e908190a8a7f14ae578fa5d |
completed | March 13, 2026, 12:04 a.m. |
Created at: March 8, 2026, 3:15 p.m.