Triple
T12903641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nelson D. Kloosterman |
E308672
|
entity |
| Predicate | languageOfTranslationTo |
P21151
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Nelson D. Kloosterman, languageOfTranslationTo, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfTranslationTo Context triple: [Nelson D. Kloosterman, languageOfTranslationTo, English]
-
A.
translationTargetLanguage
chosen
Indicates the language into which content is being or has been translated.
-
B.
languageTranslatedFrom
Indicates that a language is the source/original language from which content has been translated into another language.
-
C.
languageOfTranslations
Indicates that one entity is the language into which another entity (such as a text or work) has been translated.
-
D.
textTranslation
Indicates a relationship where one text is rendered into another language or form while preserving its original meaning.
-
E.
targetLanguage
Indicates the language that is the intended recipient or focus of a communication, translation, or linguistic operation.
- 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_69d7bdf92b588190acdf2a2291ac4590 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971820e008190bf8bc7c392c8bcbb |
completed | April 10, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69d96fa776648190b9b5c30722ea50b6 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:40 p.m.