Triple
T37560287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vladimir Nabokov’s American years |
E933800
|
entity |
| Predicate | hasLanguageOfLiteraryProduction |
P17914
|
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: [Vladimir Nabokov’s American years, hasLanguageOfLiteraryProduction, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageOfLiteraryProduction Context triple: [Vladimir Nabokov’s American years, hasLanguageOfLiteraryProduction, English]
-
A.
languageOfWritings
chosen
Indicates that a specified language is the one in which certain writings or written works are composed.
-
B.
languageWrittenAbout
Indicates that something is written about or concerning a particular language.
-
C.
wroteInMultipleLanguages
Indicates that an entity authored written works using more than one language.
-
D.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
-
E.
hasLiteraryForm
Indicates that one entity is expressed, structured, or realized in a particular literary form (such as a genre, style, or textual format).
- 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_69f76ecb4acc8190b53f96d0b013e415 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ffe23081408190a121d901dbce1403 |
completed | May 10, 2026, 1:41 a.m. |
| PD | Predicate disambiguation | batch_69ffe18aed348190912a5996b2da728b |
completed | May 10, 2026, 1:38 a.m. |
Created at: May 3, 2026, 4:17 p.m.