Triple
T27756100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love Letter worm |
E701335
|
entity |
| Predicate | affectedOrganizations |
P66747
|
FINISHED |
| Object | government agencies |
—
|
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: government agencies | Statement: [Love Letter worm, affectedOrganizations, government agencies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affectedOrganizations Context triple: [Love Letter worm, affectedOrganizations, government agencies]
-
A.
involvedOrganizations
chosen
Indicates that there is a participation or engagement relationship between an entity and one or more organizations in the context of a specific event, activity, or project.
-
B.
affectedCompany
Indicates that a company is impacted or influenced by a particular event, action, or entity.
-
C.
associatedOrgan
Indicates that one entity has a relevant connection or linkage to a particular organ, such as anatomical, functional, or pathological association.
-
D.
affectedAgency
Indicates that one entity has an effect on, or causes a change in, the agency or capacity for action of another entity.
-
E.
associatedOrganizationFocus
Indicates that an organization is linked to or concerned with a particular area of activity, topic, or domain as a primary focus.
- 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_69ef6a5193808190816eb7d0020b2d87 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f69383222c81909d8baa04129d5c81 |
completed | May 3, 2026, 12:14 a.m. |
| PD | Predicate disambiguation | batch_69f690eb1e948190aab41a89969519a5 |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 27, 2026, 4:23 p.m.