Triple
T10158592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Usenet |
E233830
|
entity |
| Predicate | spamIssue |
P92339
|
FINISHED |
| Object | experienced significant spam problems in the 1990s |
—
|
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: experienced significant spam problems in the 1990s | Statement: [Usenet, spamIssue, experienced significant spam problems in the 1990s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spamIssue Context triple: [Usenet, spamIssue, experienced significant spam problems in the 1990s]
-
A.
addressesIssue
Indicates that one entity deals with, responds to, or attempts to resolve a specific issue associated with another entity.
-
B.
sentAgainst
Indicates that something (such as a message, request, or action) is directed or dispatched in opposition to a particular target or entity.
-
C.
warningSubject
Indicates that one entity is the topic or focus of a warning issued by another entity.
-
D.
issues
Indicates that an entity formally produces, releases, or distributes something, such as a document, order, or resource, making it officially available.
-
E.
warningRecipient
Indicates that one entity is the recipient or target audience of a warning issued by another entity.
- 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_69ca848e80748190b91d1e04d35512c7 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdec56d944819081bc6ea36c905ba2 |
completed | April 2, 2026, 4:11 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba795808190acc9124c98c6e40f |
completed | April 1, 2026, 4:45 p.m. |
| PDg | Predicate description generation | batch_69cd4f8f869c8190a82ad040993e0244 |
completed | April 1, 2026, 5:02 p.m. |
Created at: March 30, 2026, 9:09 p.m.