Triple
T20774908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dustfinger |
E511329
|
entity |
| Predicate | nationalityInAdaptation |
P141471
|
FINISHED |
| Object | unspecified European |
—
|
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: unspecified European | Statement: [Dustfinger, nationalityInAdaptation, unspecified European]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalityInAdaptation Context triple: [Dustfinger, nationalityInAdaptation, unspecified European]
-
A.
televisionAdaptationCountry
Indicates the country in which a television adaptation of a work was produced or primarily created.
-
B.
nationalityInStory
Indicates that a character or entity in a narrative is associated with a particular nationality within the context of that story.
-
C.
nationalityInText
Indicates that a person's nationality is mentioned or specified within a given text.
-
D.
adaptedInLanguage
Indicates that a work or content has been modified or translated so it can be presented or understood in a specified language.
-
E.
targetNationality
Indicates that one entity has the specified nationality as its intended or designated target.
- 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_69e0b4cac7a48190a715cb3d545df2b4 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c26a39bc81909ca5d102056d8586 |
completed | April 21, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_69e5c0550ec481908a0877fb2409d983 |
completed | April 20, 2026, 5:57 a.m. |
| PDg | Predicate description generation | batch_69e5c3cbe5788190b7ace43bfdac2ef6 |
completed | April 20, 2026, 6:12 a.m. |
Created at: April 16, 2026, 12:37 p.m.