Triple
T17331909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nights of Cabiria |
E420835
|
entity |
| Predicate | criticalStatus |
P8082
|
FINISHED |
| Object | classic of world 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: classic of world cinema | Statement: [Nights of Cabiria, criticalStatus, classic of world cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: criticalStatus Context triple: [Nights of Cabiria, criticalStatus, classic of world cinema]
-
A.
criticality
Indicates the degree of importance, urgency, or potential impact associated with an entity, condition, or situation within a given context.
-
B.
criticalInterpretation
Indicates that one entity offers an evaluative, analytical, or interpretive commentary on another (such as a text, work, or idea).
-
C.
criticalReputation
chosen
Indicates that an entity is regarded by critics with a particular level or type of esteem, evaluation, or standing based on critical assessments.
-
D.
criticalStrip
Indicates that something lies within the critical strip, the region of complex values whose real parts fall between 0 and 1.
-
E.
criticalReception
Indicates how a work, performance, or product is evaluated and responded to by critics or professional reviewers.
- 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_69d889d3adc881909319f1edb8d2a956 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e439d6870c8190989897aa6beba8ff |
completed | April 19, 2026, 2:11 a.m. |
| PD | Predicate disambiguation | batch_69e3b021a5bc81909ae55406f9d0b37f |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:43 a.m.