Triple
T5693360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canadian Caper |
E125477
|
entity |
| Predicate | usedCoverStory |
P65448
|
FINISHED |
| Object | fake movie production |
—
|
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: fake movie production | Statement: [Canadian Caper, usedCoverStory, fake movie production]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedCoverStory Context triple: [Canadian Caper, usedCoverStory, fake movie production]
-
A.
usedCover
chosen
Indicates that one entity employed another entity as a protective or concealing cover in a given context.
-
B.
coverUpBy
Indicates that one entity conceals, suppresses, or hides the actions, information, or wrongdoing associated with another entity.
-
C.
coverText
Indicates that one text serves as the cover or front-facing textual representation for another work or resource.
-
D.
mediaCovered
Indicates that one entity (such as a media outlet or source) has reported on, featured, or otherwise provided coverage of another entity or event.
-
E.
originallyCoveredBy
Indicates that something was first protected, reported on, or documented by a particular source, medium, or entity before any others.
- 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_69c0082bb19c8190823a4facd3cba79b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c029014588819094a2a0f6f9b66bab |
completed | March 22, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c021c0e0408190ab6c3cd3f907e80f |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:44 p.m.