Triple
T29016037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CRIME attack |
E737308
|
entity |
| Predicate | CVEReference |
P165910
|
FINISHED |
| Object | CVE-2012-4929 |
—
|
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: CVE-2012-4929 | Statement: [CRIME attack, CVEReference, CVE-2012-4929]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: CVEReference Context triple: [CRIME attack, CVEReference, CVE-2012-4929]
-
A.
crossReference
Indicates that one entity refers the user to another related entity or source for additional or supporting information.
-
B.
symbolReferenced
Indicates that one symbol is mentioned, cited, or otherwise referred to by another symbol.
-
C.
VCCitationFor
Indicates a relationship where one item serves as a citation or reference source supporting the content or claim of another item.
-
D.
coreTextReferenced
Indicates that one text directly cites, mentions, or otherwise refers to another core text as a reference point.
-
E.
referenceType
Indicates the specific kind or category of reference relationship that one entity has to another.
- 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_69f077ee19f881909af48f9cab00a2e5 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f65fe0772881909b1fbc2e28a1206a |
completed | May 2, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69f659d297cc8190b2b962ba30a1edb3 |
completed | May 2, 2026, 8:08 p.m. |
| PDg | Predicate description generation | batch_69f65ad638ac8190a17bb987fce53279 |
completed | May 2, 2026, 8:13 p.m. |
Created at: April 28, 2026, 9:45 a.m.