Triple
T14396231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mikkel Svane |
E356954
|
entity |
| Predicate | hasBusinessModelExperience |
P106179
|
FINISHED |
| Object | subscription 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 software | Statement: [Mikkel Svane, hasBusinessModelExperience, subscription software]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBusinessModelExperience Context triple: [Mikkel Svane, hasBusinessModelExperience, subscription software]
-
A.
hasBusinessModelCharacteristic
Indicates that a business model possesses or exhibits a specific feature, quality, or attribute.
-
B.
businessModelWorkedOn
chosen
Indicates that an entity has actively developed, contributed to, or worked on a particular business model.
-
C.
hasBusiness
Indicates that one entity owns, operates, or is formally associated with a business entity.
-
D.
usesBusinessModel
Indicates that one entity operates according to, or applies in practice, the business model defined or provided by another entity.
-
E.
hasGlobalExperience
Indicates that an entity possesses experience gained from working, operating, or engaging across multiple countries or international contexts.
- 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.