Triple
T36144212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Night Train to Lisbon |
E1045398
|
entity |
| Predicate | novelOriginalLanguage |
P74798
|
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: [Night Train to Lisbon, novelOriginalLanguage, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: novelOriginalLanguage Context triple: [Night Train to Lisbon, novelOriginalLanguage, German]
-
A.
workInOriginalLanguage
Indicates that a work is being created, presented, or studied in the language in which it was originally produced, without translation.
-
B.
originalLanguagePublisher
Indicates that a publisher is responsible for releasing a work in its original language, before or apart from any translations.
-
C.
shortStoryOriginalLanguage
Indicates the original language in which a short story was first written or published.
-
D.
originalLanguageTitle
Indicates the title of a work as it appears in its original language of creation or publication.
-
E.
originalLanguageOfWholeWork
chosen
Indicates that a given language is the primary or original language in which an entire work (such as a book, film, or other complete creation) was first produced or expressed.
- 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_69f76e37ace88190a906b107d388f5d1 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b3e2f3c08190be4fd1ae4fa1266d |
completed | May 3, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bcc47081909fe7d592ac69006c |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 3, 2026, 4:08 p.m.