Triple
T2215751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sharon Maguire |
E48027
|
entity |
| Predicate | hasGenreInFilmography |
P14417
|
FINISHED |
| Object | romantic comedy |
—
|
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: romantic comedy | Statement: [Sharon Maguire, hasGenreInFilmography, romantic comedy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenreInFilmography Context triple: [Sharon Maguire, hasGenreInFilmography, romantic comedy]
-
A.
hasGenreArtist
Indicates that an artist is associated with or specializes in a particular genre.
-
B.
workedOnGenre
chosen
Indicates that an entity (such as a person or organization) has done work related to a particular genre.
-
C.
coveredInGenre
Indicates that a work or item is associated with, categorized under, or treated within a particular genre.
-
D.
hasGenreInfluenceOn
Indicates that one genre has a notable impact on shaping or influencing the characteristics, style, or development of another genre.
-
E.
hasNotableGenre
Indicates that an entity is significantly associated with a particular genre, such that the genre is especially characteristic or noteworthy for that entity.
- 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_69a88aa1ee708190862c8c378c41e9eb |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbff11574819091d1b50d637ae767 |
completed | March 7, 2026, 6:04 a.m. |
| PD | Predicate disambiguation | batch_69abbdaa26d48190860c33fd464c4845 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.