Triple
T34229910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Law, UB |
E878160
|
entity |
| Predicate | educatesForOccupation |
P335
|
FINISHED |
| Object | lawyer |
—
|
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: lawyer | Statement: [Faculty of Law, UB, educatesForOccupation, lawyer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: educatesForOccupation Context triple: [Faculty of Law, UB, educatesForOccupation, lawyer]
-
A.
educatesForSector
Indicates that an entity provides education or training specifically aimed at preparing individuals for a particular sector or industry.
-
B.
educationAspiration
Indicates an individual's intended or desired level of education or educational achievement.
-
C.
educates
chosen
Indicates that one entity provides instruction, knowledge, or training to another entity.
-
D.
possibleEducation
Indicates that an entity is a plausible or potential educational attainment or qualification for another entity, without asserting that it actually occurred.
-
E.
educationField
Indicates the academic or professional discipline in which an entity has been educated or trained.
- 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_69f349b16d0481908754e3069f05e0c1 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f757898fe48190b124dc7301672623 |
completed | May 3, 2026, 2:11 p.m. |
| PD | Predicate disambiguation | batch_69f754c484348190948d2a04ff228fb1 |
completed | May 3, 2026, 1:59 p.m. |
Created at: May 1, 2026, 1:56 a.m.