Triple
T11764395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Flame of Life |
E279743
|
entity |
| Predicate | originatesInFilmIndustry |
P101250
|
FINISHED |
| Object | Italian 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: Italian cinema | Statement: [The Flame of Life, originatesInFilmIndustry, Italian cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originatesInFilmIndustry Context triple: [The Flame of Life, originatesInFilmIndustry, Italian cinema]
-
A.
hasFilmIndustryCenter
Indicates that a location serves as a primary hub or central base for activities related to the film industry.
-
B.
usedInProductionOfFilm
Indicates that something (such as a resource, tool, or material) was utilized during the making or production process of a film.
-
C.
basedInFilm
Indicates that something (such as a character, event, or work) is situated, set, or primarily located within the context or universe of a particular film.
-
D.
hasMediaIndustry
Indicates that an entity is involved in, associated with, or operates within the media industry.
-
E.
hasAwardedForFilmIndustry
Indicates that an entity has given or conferred an award to another entity specifically for achievements in the film industry.
- 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_69d6ab01d2688190ad8ed6bda487eaa5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a5248e0881909ed1b4df7be422f7 |
completed | April 10, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69d88a829fe481909cc5431de7d6058e |
completed | April 10, 2026, 5:28 a.m. |
| PDg | Predicate description generation | batch_69d890467a2481909ce6c669e739c8de |
completed | April 10, 2026, 5:53 a.m. |
Created at: April 8, 2026, 9:41 p.m.