Triple
T3826749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinese American cinema |
E88707
|
entity |
| Predicate | periodOfSignificantGrowth |
P6451
|
FINISHED |
| Object | late 20th century |
—
|
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: late 20th century | Statement: [Chinese American cinema, periodOfSignificantGrowth, late 20th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: periodOfSignificantGrowth Context triple: [Chinese American cinema, periodOfSignificantGrowth, late 20th century]
-
A.
hadGrowthPeriod
Indicates that an entity experienced a specific span of time during which it underwent growth or development.
-
B.
growthProperty
Indicates that one entity characterizes, constrains, or quantifies how another entity grows or changes in magnitude over some parameter (such as time, size, or input).
-
C.
timePeriodOfMajorExpansion
chosen
Indicates the time span during which the referenced entity underwent its most significant growth or expansion.
-
D.
growthType
Indicates the manner or pattern in which something develops or increases over time.
-
E.
hasGrowthRate
Indicates the rate at which something increases in size, quantity, or value over a given period of time.
- 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_69aed9538cf881909d9ce8ca4ac7c18c |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeeb8459f881908a2c91bb07e381ef |
completed | March 9, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69aee74c2e04819094b94b3c0bac1806 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:17 p.m.