Triple
T33873147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Film Capital Europe Funds |
E868276
|
entity |
| Predicate | benefitsToProjects |
P180100
|
FINISHED |
| Object | access to production capital |
—
|
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: access to production capital | Statement: [Film Capital Europe Funds, benefitsToProjects, access to production capital]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefitsToProjects Context triple: [Film Capital Europe Funds, benefitsToProjects, access to production capital]
-
A.
benefitsAre
Indicates that certain advantages, gains, or positive outcomes are possessed by or accrue to a particular entity or group.
-
B.
benefits
Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or action.
-
C.
benefitsArea
Indicates that one entity provides advantages, improvements, or positive effects to a specified area or region.
-
D.
eligibleProject
Indicates that a project satisfies the required conditions or criteria to qualify for a particular status, process, or benefit.
-
E.
sectorBenefited
Indicates that a particular sector gains advantage, support, or positive impact from a given action, policy, resource, or entity.
- 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_69f34995029081909ede0f7df73d1a5e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
| PDg | Predicate description generation | batch_69f730890a008190a882f7828f1c9162 |
completed | May 3, 2026, 11:24 a.m. |
Created at: May 1, 2026, 1:47 a.m.