Triple
T38241436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hartbeat Productions |
E1013769
|
entity |
| Predicate | producedProgrammingType |
P193720
|
FINISHED |
| Object | children's art series |
—
|
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: children's art series | Statement: [Hartbeat Productions, producedProgrammingType, children's art series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: producedProgrammingType Context triple: [Hartbeat Productions, producedProgrammingType, children's art series]
-
A.
producedFilmType
Indicates that an entity (such as a person or organization) was responsible for producing a film of a specified type or category.
-
B.
producedSeriesGenre
chosen
Indicates that a producer or production entity created or was responsible for a television or film series belonging to a specified genre.
-
C.
notableProductionType
Indicates that the subject is particularly known for producing or creating instances of the specified type.
-
D.
producedProgram
Indicates that one entity created or produced a specific program (such as a TV show, software, or other structured content).
-
E.
filmProductionType
Indicates the specific kind or category of production under which a film was made (e.g., feature, short, documentary, TV movie).
- 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_69f76dd72a248190a5fe18db2bd1eb15 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff59b33a38819086cc9aa19b81748b |
completed | May 9, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69ff587758f88190a39c2164341dc554 |
completed | May 9, 2026, 3:53 p.m. |
Created at: May 3, 2026, 4:30 p.m.