Triple
T276886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trump University |
E5268
|
entity |
| Predicate | offered |
P178
|
FINISHED |
| Object | real estate 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: real estate seminars | Statement: [Trump University, offered, real estate seminars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offered Context triple: [Trump University, offered, real estate seminars]
-
A.
firstOffered
Indicates that one entity was the earliest or initial provider or proposer of something to another entity or context.
-
B.
offersViewOf
Indicates that one entity provides a vantage point from which another entity can be seen or visually appreciated.
-
C.
offersProgram
chosen
Indicates that an entity provides or makes available a specific program (such as a course, curriculum, or initiative).
-
D.
offersActivity
Indicates that one entity provides or makes available a specific activity for another entity to participate in or use.
-
E.
availableAs
Indicates that one entity can be used, accessed, or offered in the form, role, or capacity of another 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_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.