Triple
T14396291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ZEN |
E356956
|
entity |
| Predicate | relatedCompanyBusinessModel |
P15707
|
FINISHED |
| Object | subscription-based software |
—
|
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: subscription-based software | Statement: [ZEN, relatedCompanyBusinessModel, subscription-based software]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedCompanyBusinessModel Context triple: [ZEN, relatedCompanyBusinessModel, subscription-based software]
-
A.
associatedCompanyBusinessModel
chosen
Indicates that there is a relationship linking a company to the specific business model it follows or employs.
-
B.
associatedCompanyBusinessSegment
Indicates that a company is linked to a specific business segment through its operations, products, or services.
-
C.
hasUnderlyingCompanyBusinessModel
Indicates that one entity possesses or is based on a specific company business model that underlies its structure, operations, or value creation.
-
D.
associatedCompanyGlobalScope
Indicates that there is a relationship linking an entity to a company at a global (worldwide) organizational scope.
-
E.
associatedCompanySpecialization
Indicates that a company is linked to a particular area of specialization or expertise.
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90826f908190b3969af9b7cf922f |
completed | April 14, 2026, 7:07 p.m. |
| PD | Predicate disambiguation | batch_69de2aa024c48190805df6a9d63deb10 |
completed | April 14, 2026, 11:53 a.m. |
Created at: April 10, 2026, 1:17 a.m.