Triple
T27383698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catozzo splicing machine |
E691304
|
entity |
| Predicate | usedWorldwideIn |
P11850
|
FINISHED |
| Object | film editing |
—
|
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: film editing | Statement: [Catozzo splicing machine, usedWorldwideIn, film editing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedWorldwideIn Context triple: [Catozzo splicing machine, usedWorldwideIn, film editing]
-
A.
usedWorldwide
chosen
Indicates that something is utilized or applied across many countries or regions around the world.
-
B.
usedInCountries
Indicates that something is utilized or applied within one or more specified countries.
-
C.
usedInCountry
Indicates that something is utilized, applied, or in operation within the specified country.
-
D.
usedInAllRegionsOf
Indicates that something is utilized or applied in every region within a specified scope or system.
-
E.
usedByCountriesWith
Indicates that something (such as an item, system, or practice) is utilized or employed by one or more specified countries in common.
- 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_69ef52022538819081f873d0c84a6dd6 |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651a931748190a637e631a52bbfaa |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 27, 2026, 12:23 p.m.