Triple
T3036707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacek Majchrowski |
E83026
|
entity |
| Predicate | typeOfScholar |
P43012
|
FINISHED |
| Object | legal historian |
—
|
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: legal historian | Statement: [Jacek Majchrowski, typeOfScholar, legal historian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfScholar Context triple: [Jacek Majchrowski, typeOfScholar, legal historian]
-
A.
academicType
Indicates the specific academic category or classification associated with an entity (such as a work, program, or role).
-
B.
typeOfScientist
chosen
Indicates that one entity is a scientist and the other specifies the kind or specialization of that scientist.
-
C.
scholarshipType
Indicates the specific category or kind of scholarship associated with an entity.
-
D.
thesisType
Indicates the specific category or kind of thesis associated with an academic work or degree.
-
E.
hasNotableScholar
Indicates that an entity is associated with a scholar who is recognized as particularly distinguished or influential in relation to that entity.
- 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_69ad8b2298908190a7cb4e9bdbf064d0 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9b2cd4988190b52fe3616ecbe9ef |
completed | March 8, 2026, 3:52 p.m. |
| PD | Predicate disambiguation | batch_69ad961e2a408190afb1759132701305 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:01 p.m.