Triple
T480865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coursera |
E9162
|
entity |
| Predicate | hasUserInterface |
P12981
|
FINISHED |
| Object | website |
—
|
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: website | Statement: [Coursera, hasUserInterface, website]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUserInterface Context triple: [Coursera, hasUserInterface, website]
-
A.
userInterface
Indicates a relationship where one entity serves as the interface or interaction layer through which a user engages with another system, service, or resource.
-
B.
hasInterface
chosen
Indicates that one entity provides, exposes, or is connected through a defined interface to another entity.
-
C.
usesInterface
Indicates that one entity interacts with or operates another entity through a specified interface or set of interface methods.
-
D.
hasUser
Indicates that an entity is associated with or linked to a specific user.
-
E.
hasUserService
Indicates that an entity is associated with or utilizes a particular user-related service.
- 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_69a2e7ff81708190b0507a24a997232c |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f058ebe48190aaa0a829b21f75fa |
completed | Feb. 28, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69a2edf321288190b5d560f75782c2cb |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.