Triple
T28406840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CEO of Huawei |
E719550
|
entity |
| Predicate | hasEmployerBusinessArea |
P66997
|
FINISHED |
| Object | 5G infrastructure |
—
|
LITERAL 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: 5G infrastructure | Statement: [CEO of Huawei, hasEmployerBusinessArea, 5G infrastructure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmployerBusinessArea Context triple: [CEO of Huawei, hasEmployerBusinessArea, 5G infrastructure]
-
A.
isPartOfBusinessArea
Indicates that one entity belongs to, is included within, or falls under the scope of a particular business area.
-
B.
hasKeyBusinessArea
chosen
Indicates that an entity is associated with or operates within a particular primary business area or domain.
-
C.
businessAreaExpanded
Indicates that the scope or coverage of a business area has been increased or broadened beyond its previous boundaries.
-
D.
hasBusinessIn
Indicates that one entity conducts, operates, or maintains business activities within the jurisdiction, location, or domain of another entity.
-
E.
primaryBusinessArea
Indicates the main field, sector, or domain in which an entity primarily conducts its business activities.
- F. None of above.
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_69eff6f0f37c8190b37bc6fab08a9449 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f65a6c900881908f18b61273d7bf8d |
completed | May 2, 2026, 8:11 p.m. |
| PD | Predicate disambiguation | batch_69f659ce58408190ba9e007b4810d4d0 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 1:24 a.m.