Triple
T36086115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mood Swings |
E1043783
|
entity |
| Predicate | producerCountryOfCitizenship |
P198590
|
FINISHED |
| Object | Canada |
—
|
NE NERFINISHED |
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: Canada | Statement: [Mood Swings, producerCountryOfCitizenship, Canada]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: producerCountryOfCitizenship Context triple: [Mood Swings, producerCountryOfCitizenship, Canada]
-
A.
creatorCountryOfCitizenship
Indicates the country in which the creator holds or held legal citizenship.
-
B.
countryOfCitizenship
Indicates the country in which a person or entity holds legal citizenship.
-
C.
possibleCountryOfCitizenship
Indicates that an entity could plausibly be a country in which the person or agent may hold, or be eligible to hold, citizenship.
-
D.
definedCitizenship
Indicates that a formal citizenship status has been legally established or specified for an entity.
-
E.
stateOfCitizenship
Indicates the legal nationality or country to which a person formally belongs as a citizen.
- 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_69f76e3154908190a6f702671c2bea08 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fef3ceef648190b58027c93d757438 |
completed | May 9, 2026, 8:43 a.m. |
| PD | Predicate disambiguation | batch_69fef359da2c819091a034387b08821f |
completed | May 9, 2026, 8:42 a.m. |
| PDg | Predicate description generation | batch_69fef3cdea708190af41c1ff23b68f88 |
completed | May 9, 2026, 8:43 a.m. |
Created at: May 3, 2026, 4:08 p.m.