Triple
T14374491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 0992.HK |
E356438
|
entity |
| Predicate | primaryBusinessOfIssuer |
P64615
|
FINISHED |
| Object | personal computers |
—
|
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: personal computers | Statement: [0992.HK, primaryBusinessOfIssuer, personal computers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryBusinessOfIssuer Context triple: [0992.HK, primaryBusinessOfIssuer, personal computers]
-
A.
primaryBusinessArea
Indicates the main field, sector, or domain in which an entity primarily conducts its business activities.
-
B.
issuerBusinessType
Indicates the category or nature of business activity that the issuing entity is engaged in.
-
C.
underlyingCompanyBusinessFocus
Indicates the primary industry, sector, or type of business activity that the underlying company is focused on.
-
D.
hasIssuerPrimaryBusiness
chosen
Indicates that an entity’s main or primary line of business is identified or characterized by the associated business activity or classification.
-
E.
industryOfUnderlyingIssuer
Indicates the industry sector to which the underlying issuer in a financial or contractual arrangement belongs.
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9007184c8190aebb003cb6548cc8 |
completed | April 14, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69de2a9cb3e081909f6b33fdd939bb9e |
completed | April 14, 2026, 11:53 a.m. |
Created at: April 10, 2026, 1:16 a.m.