Triple
T5791537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Journey to Italy |
E128404
|
entity |
| Predicate | cinematicSignificance |
P65857
|
FINISHED |
| Object | landmark of modern cinema |
—
|
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: landmark of modern cinema | Statement: [Journey to Italy, cinematicSignificance, landmark of modern cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cinematicSignificance Context triple: [Journey to Italy, cinematicSignificance, landmark of modern cinema]
-
A.
cinematicContext
Indicates the relationship in which something is situated within, shaped by, or relevant to the circumstances, style, or conventions of cinema or film.
-
B.
cinemaInfluence
Indicates how one entity affects or shapes another through the medium of cinema, such as films, filmmaking, or cinematic culture.
-
C.
cinematographyBy
Indicates that the cinematographic work (such as the camera work or visual style of a film or video) is created or supervised by a specified person or entity.
-
D.
cinematographyAwardedTo
Indicates that a cinematography-related award has been given to a particular recipient (such as a person or team) for their work.
-
E.
popularFilmIndustry
Indicates that an entity has a widely recognized and well-liked film industry that attracts significant audience interest and attention.
- 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_69c00845ca68819081a2ce3ecca577f7 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02a56c73c81908a1c72c86e474b54 |
completed | March 22, 2026, 5:43 p.m. |
| PD | Predicate disambiguation | batch_69c021d2cd608190b98a7e3aa7001d27 |
completed | March 22, 2026, 5:07 p.m. |
| PDg | Predicate description generation | batch_69c024861bc88190a17782c1982fbb3e |
completed | March 22, 2026, 5:19 p.m. |
Created at: March 22, 2026, 3:51 p.m.