Triple
T32993945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Story of Joanna |
E844169
|
entity |
| Predicate | countryClassification |
P202410
|
FINISHED |
| Object | American film |
—
|
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: American film | Statement: [The Story of Joanna, countryClassification, American film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryClassification Context triple: [The Story of Joanna, countryClassification, American film]
-
A.
regionClassification
Indicates how a given area or location is categorized into a specific region based on defined criteria or boundaries.
-
B.
countryType
Indicates the classification or category of a country based on a specified typology (e.g., political, economic, or geographic type).
-
C.
regionallyClassifiedAs
Indicates that something is assigned to or identified with a specific geographic or regional category.
-
D.
countryStatus
Indicates the political or legal condition of a country, such as its sovereignty, recognition, or current state in international or domestic contexts.
-
E.
rangeCountries
Indicates the set of countries over which something (such as a service, product, or data coverage) is available, applicable, or valid.
- 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_69f3494d99988190b502c68926af2c4d |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a007aa8d3a481908543f9b5d562a90c |
completed | May 10, 2026, 12:31 p.m. |
| PD | Predicate disambiguation | batch_6a007a44996481908688ccfdbc56511d |
completed | May 10, 2026, 12:29 p.m. |
| PDg | Predicate description generation | batch_6a007aa82810819080bb16dd5022c324 |
completed | May 10, 2026, 12:31 p.m. |
Created at: May 1, 2026, 1:22 a.m.