Triple
T34909254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roger Hargreaves |
E1006818
|
entity |
| Predicate | booksTranslatedInto |
P65939
|
FINISHED |
| Object | multiple languages |
—
|
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: multiple languages | Statement: [Roger Hargreaves, booksTranslatedInto, multiple languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: booksTranslatedInto Context triple: [Roger Hargreaves, booksTranslatedInto, multiple languages]
-
A.
widelyTranslated
chosen
Indicates that a work has been translated into many different languages or versions, reflecting broad international dissemination.
-
B.
includesTranslatedWorks
Indicates that one entity contains or encompasses works that have been translated from their original language.
-
C.
hasWorkTranslatedInto
Indicates that a work has been translated into a specified language or target work.
-
D.
genreTranslated
Indicates that the genre of a work has been translated or adapted from its original form into another language or cultural context.
-
E.
languageOfBooks
Indicates the language in which the referenced books are written or published.
- 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_69f76dc1b4a081909b4c6e4d8ec0aa2d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782c98fa08190870b68de2c1ff26a |
completed | May 3, 2026, 5:15 p.m. |
| PD | Predicate disambiguation | batch_69f781020cc4819088c40cb8589504e4 |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.