Triple
T3374890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olbrich Botanical Gardens |
E71042
|
entity |
| Predicate | Michael B. OlbrichOccupation |
P12884
|
FINISHED |
| Object | Madison attorney |
—
|
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: Madison attorney | Statement: [Olbrich Botanical Gardens, Michael B. OlbrichOccupation, Madison attorney]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Michael B. OlbrichOccupation Context triple: [Olbrich Botanical Gardens, Michael B. OlbrichOccupation, Madison attorney]
-
A.
designerOccupation
Indicates that one entity serves as the professional designer or design specialist for another entity.
-
B.
namedPersonOccupation
chosen
Indicates that a person is explicitly identified as having a particular occupation or job role.
-
C.
creatorOccupation
Indicates the professional role or job that the creator of an entity holds or held.
-
D.
founderKnownFor
Indicates that a founder is particularly recognized or notable for a specific work, achievement, product, or contribution.
-
E.
authorOccupation
Indicates the professional role or job that an author holds or is associated with.
- 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_69ad85a7f80c8190a05e43013f298942 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb2e5fc6c81909ff582611751096d |
completed | March 8, 2026, 5:33 p.m. |
| PD | Predicate disambiguation | batch_69ada433059881908e46f38cc5f40a32 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:13 p.m.