Triple
T7895137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anna Kournikova virus |
E183325
|
entity |
| Predicate | attachmentFileName |
P33859
|
FINISHED |
| Object | AnnaKournikova.jpg.vbs |
—
|
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: AnnaKournikova.jpg.vbs | Statement: [Anna Kournikova virus, attachmentFileName, AnnaKournikova.jpg.vbs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attachmentFileName Context triple: [Anna Kournikova virus, attachmentFileName, AnnaKournikova.jpg.vbs]
-
A.
fileName
chosen
Indicates the name assigned to a file, typically used to identify or reference that file within a system or context.
-
B.
documentationName
Indicates the name or title assigned to a specific piece of documentation.
-
C.
attachmentMethod
Indicates the way or technique by which one entity is fastened, joined, or secured to another.
-
D.
hasAttachmentOrgan
Indicates that one entity possesses a specific anatomical or structural organ used to attach, anchor, or fasten it to another entity or substrate.
-
E.
labelFile
Indicates assigning a descriptive label or tag to a file.
- 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_69ca828c474c8190a254d6499871eaff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a174574819084270dbb6fcbb7fe |
completed | March 31, 2026, 3:05 a.m. |
| PD | Predicate disambiguation | batch_69cae92d94448190b4425bbfb64c658c |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:01 p.m.