Triple
T3727911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | YouView |
E78992
|
entity |
| Predicate | hasPartner |
P1136
|
FINISHED |
| Object | Huawei |
E61521
|
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: Huawei | Statement: [YouView, hasPartner, Huawei]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Huawei Context triple: [YouView, hasPartner, Huawei]
-
A.
Huawei
chosen
Huawei is a major Chinese multinational technology company best known globally for its telecommunications equipment, smartphones, and role in 5G network infrastructure.
-
B.
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.
-
C.
Nokia
Nokia is a Finnish multinational telecommunications and consumer electronics company best known for its historic leadership in mobile phones and its current focus on network infrastructure and 5G technologies.
-
D.
Xiaomi
Xiaomi is a major Chinese electronics and smartphone manufacturer known for its affordable, feature-rich devices and rapidly growing global presence.
-
E.
Ericsson
Ericsson is a Swedish multinational telecommunications company known for providing mobile network infrastructure, services, and software to 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_69ad8b0e4650819090ad7cef094285e8 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcaf921bc81908bb347d6b9204670 |
completed | March 8, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4db1102a08190b5965c474dfab6db |
completed | March 14, 2026, 3:50 a.m. |
Created at: March 8, 2026, 3:34 p.m.