Triple
T276912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trump University |
E5268
|
entity |
| Predicate | courseFormat |
P7876
|
FINISHED |
| Object | live seminars |
—
|
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: live seminars | Statement: [Trump University, courseFormat, live seminars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: courseFormat Context triple: [Trump University, courseFormat, live seminars]
-
A.
courseType
Indicates the classification or category of a course based on its nature, level, or instructional format.
-
B.
offersEducationMode
chosen
Indicates that an entity provides a particular mode or format in which education or instruction is delivered.
-
C.
format
Indicates the specific arrangement, structure, or presentation style in which something is organized or expressed.
-
D.
offersCourseType
Indicates that an entity provides or makes available a course of a specified type.
-
E.
educationSystem
Indicates the relationship in which an entity is part of, governed by, or operates within a particular system or structure of education.
- 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25ded68c88190b1fc595ce329aeb9 |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b7480e881909399beccfc7ffb81 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.