Triple
T10245809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gratitude International |
E240208
|
entity |
| Predicate | workGenreFocus |
P14417
|
FINISHED |
| Object | comedy films |
—
|
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: comedy films | Statement: [Gratitude International, workGenreFocus, comedy films]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workGenreFocus Context triple: [Gratitude International, workGenreFocus, comedy films]
-
A.
formerGenreFocus
Indicates that an entity previously concentrated on or specialized in a particular genre, but no longer does so.
-
B.
basedOnWorkGenre
Indicates that one entity’s genre classification is derived from or determined by the genre of another work.
-
C.
workedOnGenre
chosen
Indicates that an entity (such as a person or organization) has done work related to a particular genre.
-
D.
genreWithin
Indicates that one genre is a subgenre or more specific category contained within another, broader genre.
-
E.
awardGenreFocus
Indicates that an award specifically recognizes or emphasizes works within a particular genre.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d328272c8190a3548d7f7f38cfc4 |
completed | April 7, 2026, 9:49 a.m. |
| PD | Predicate disambiguation | batch_69d4d1ebd6c88190a1f3f4a72a99d6fe |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:26 a.m.