Triple
T15065940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marnix van Rij |
E379754
|
entity |
| Predicate | hasProfessionalBackground |
P55248
|
FINISHED |
| Object | tax consultancy |
—
|
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: tax consultancy | Statement: [Marnix van Rij, hasProfessionalBackground, tax consultancy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProfessionalBackground Context triple: [Marnix van Rij, hasProfessionalBackground, tax consultancy]
-
A.
hasProfessionalStatus
Indicates that an entity holds a particular professional standing, rank, or qualification within a field or occupation.
-
B.
hasProfessionalSection
Indicates that an entity includes or is associated with a designated professional section, division, or category within its structure or content.
-
C.
hasAcademicBackgroundIn
Indicates that an entity possesses formal education, training, or scholarly experience in a specified academic field or discipline.
-
D.
hasProfessionalOrientation
chosen
Indicates that an entity is directed toward, focused on, or aligned with a particular profession, career field, or occupational domain.
-
E.
hasPastOccupation
Indicates that an entity previously held a particular job, role, or occupation in the past.
- 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dedeea750c819082d8823c9ab6c5a2 |
completed | April 15, 2026, 12:42 a.m. |
| PD | Predicate disambiguation | batch_69deb95a182081908fffc4402b02a394 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:02 a.m.