Triple
T24644562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baron Georg Heinrich Thyssen-Bornemisza |
E610068
|
entity |
| Predicate | hasFamilyBusinessIn |
P156890
|
FINISHED |
| Object | art collecting |
—
|
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: art collecting | Statement: [Baron Georg Heinrich Thyssen-Bornemisza, hasFamilyBusinessIn, art collecting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFamilyBusinessIn Context triple: [Baron Georg Heinrich Thyssen-Bornemisza, hasFamilyBusinessIn, art collecting]
-
A.
hasFamilyBusinessIn
chosen
Indicates that an entity owns, operates, or is significantly involved in a family-run business located in a specified place.
-
B.
relatedFamilyBusiness
Indicates that there is a connection between entities through ownership, management, or involvement in the same family-run business or businesses.
-
C.
hasBusiness
Indicates that one entity owns, operates, or is formally associated with a business entity.
-
D.
hasBusinessIn
Indicates that one entity conducts, operates, or maintains business activities within the jurisdiction, location, or domain of another entity.
-
E.
hasBusinesses
Indicates that an entity owns, operates, or is associated with one or more businesses.
- 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_69e2c4d350a481909170482bc2ce6af9 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f422aee0408190899efe7e24ef2b40 |
completed | May 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f420e92cc88190a803aecdae78a051 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 2:33 a.m.