Triple
T33826635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Latin American cinema |
E866972
|
entity |
| Predicate | hadMajorExpansionIn |
P69521
|
FINISHED |
| Object | 1960s |
—
|
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: 1960s | Statement: [Latin American cinema, hadMajorExpansionIn, 1960s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadMajorExpansionIn Context triple: [Latin American cinema, hadMajorExpansionIn, 1960s]
-
A.
majorExpansionUnder
Indicates that one entity is undergoing or has undergone a significant enlargement, growth, or extension while being under the authority, control, or scope of another entity.
-
B.
hasExpansion
Indicates that one entity serves as a larger, extended, or elaborated form of another entity.
-
C.
hasGeographicExpansion
Indicates that an entity has extended its presence, influence, or operations into additional geographic areas beyond its original location.
-
D.
hasUrbanExpansionTo
Indicates that an urban area has expanded or extended its development into another specified area or region.
-
E.
historicalPeriodOfExpansion
chosen
Indicates a historical period during which the referenced entity underwent significant growth, enlargement, or territorial/organizational expansion.
- 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_69f34991dd248190a659541588506b3c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7001d25608190a7b028bdbfa6e221 |
completed | May 3, 2026, 7:58 a.m. |
| PD | Predicate disambiguation | batch_69f6fc59518081908b0275f47721d561 |
completed | May 3, 2026, 7:42 a.m. |
Created at: May 1, 2026, 1:46 a.m.