Triple
T4599723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation Silver Fox |
E100292
|
entity |
| Predicate | originalCodenameLanguage |
P28203
|
FINISHED |
| Object | German |
—
|
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: German | Statement: [Operation Silver Fox, originalCodenameLanguage, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalCodenameLanguage Context triple: [Operation Silver Fox, originalCodenameLanguage, German]
-
A.
hasCodenameLanguage
Indicates that a codename is expressed or defined in a particular language.
-
B.
translationOfCodename
Indicates that one codename is a translated version of another codename, preserving its intended meaning across languages.
-
C.
relatedCodename
Indicates that one entity has an associated or connected codename that is contextually related to it.
-
D.
originalNameLanguage
chosen
Indicates that the specified language is the language in which an entity’s original or primary name was expressed.
-
E.
languageName
Indicates the specific name assigned to a language in the relationship.
- 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_69bd43cbc014819098b45f435908f88a |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5971f448819090f6e76c7d3ffc2d |
completed | March 20, 2026, 2:28 p.m. |
| PD | Predicate disambiguation | batch_69bd522c811c81909aae4feadae33174 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:11 p.m.