Triple
T6493068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cortona |
E148087
|
entity |
| Predicate | inFilm |
P17240
|
FINISHED |
| Object | featured in the film adaptation of "Under the Tuscan Sun" |
—
|
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: featured in the film adaptation of "Under the Tuscan Sun" | Statement: [Cortona, inFilm, featured in the film adaptation of "Under the Tuscan Sun"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inFilm Context triple: [Cortona, inFilm, featured in the film adaptation of "Under the Tuscan Sun"]
-
A.
filmBase
Indicates the primary location or headquarters from which a film-related entity (such as a production, company, or operation) is based or operates.
-
B.
inFilmAndTV
chosen
Indicates that the subject appears or is featured within the context of film and television works.
-
C.
film
Indicates that an entity is a movie or cinematic work, or that a relationship involves such a movie.
-
D.
filmMedium
Indicates the physical or technical format (such as film stock, digital, or video) in which a film is recorded or presented.
-
E.
cinemaOf
Indicates a relationship where a cinema is associated with, belongs to, or is located within a particular place, organization, or context.
- 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_69c009088f3081909cd467b05919de30 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06ab6abbc8190a4971ad5a654b0cd |
completed | March 22, 2026, 10:18 p.m. |
| PD | Predicate disambiguation | batch_69c06740bebc81909d9d6956baa2bcb9 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:53 p.m.