Triple
T1086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MIT OpenCourseWare |
E22
|
entity |
| Predicate | offers |
P178
|
FINISHED |
| Object | free course materials |
—
|
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: free course materials | Statement: [MIT OpenCourseWare, offers, free course materials]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offers Context triple: [MIT OpenCourseWare, offers, free course materials]
-
A.
offersProgram
chosen
Indicates that an entity provides or makes available a specific program (such as a course, curriculum, or initiative).
-
B.
proposes
Indicates that one entity formally suggests or puts forward an idea, plan, or course of action to another entity for consideration or approval.
-
C.
offersDegree
Indicates that an institution or program provides a specific academic degree as an available qualification.
-
D.
complements
Indicates that one entity enhances, completes, or improves another by providing qualities or functions that fit well together.
-
E.
allows
Indicates that one entity grants permission, capability, or opportunity for another entity to perform an action or be in a certain state.
- 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_69a22a285828819081a58308fb963df1 |
completed | Feb. 27, 2026, 11:35 p.m. |
| NER | Named-entity recognition | batch_69a23344daf8819083118bbac5f46568 |
completed | Feb. 28, 2026, 12:13 a.m. |
| PD | Predicate disambiguation | batch_69a232e52e7c81909c072703e28e8c61 |
completed | Feb. 28, 2026, 12:12 a.m. |
Created at: Feb. 27, 2026, 11:36 p.m.