Triple
T29789803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kim Kardashian "Break the Internet" Paper magazine cover |
E756369
|
entity |
| Predicate | hasCoverLine |
P202644
|
FINISHED |
| Object | Paper Winter 2014 |
—
|
NE NERFINISHED |
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: Paper Winter 2014 | Statement: [Kim Kardashian "Break the Internet" Paper magazine cover, hasCoverLine, Paper Winter 2014]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCoverLine Context triple: [Kim Kardashian "Break the Internet" Paper magazine cover, hasCoverLine, Paper Winter 2014]
-
A.
hasCoverFeature
Indicates that one entity serves as a prominent or featured element on the cover of another entity (such as a publication, product, or media item).
-
B.
hasCoverType
Indicates that one entity possesses or is associated with a specific type or category of cover.
-
C.
hasCoverName
Indicates that one entity uses or is known by an alternative, often secret or assumed, name in relation to another entity or context.
-
D.
containsCoverOf
Indicates that one entity includes within it a cover or covering representation of another entity.
-
E.
hasCoverage
Indicates that one entity provides insurance or protection coverage for another entity or subject.
- F. None of above. chosen
Provenance (4 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_69f22451fb748190bbdbab401280affb |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_6a00a602b6b48190a9dea8ae22d2fa05 |
completed | May 10, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_6a00a559bf3881909a7b50776d8f47bb |
completed | May 10, 2026, 3:33 p.m. |
| PDg | Predicate description generation | batch_6a00a601ff988190b3eb7a9abc92a557 |
completed | May 10, 2026, 3:36 p.m. |
Created at: April 29, 2026, 5:11 p.m.