Triple
T20618717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love Serenade |
E506639
|
entity |
| Predicate | awardCategoryWon |
P1619
|
FINISHED |
| Object | Best First Feature Film at Cannes (Caméra d'Or) |
—
|
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: Best First Feature Film at Cannes (Caméra d'Or) | Statement: [Love Serenade, awardCategoryWon, Best First Feature Film at Cannes (Caméra d'Or)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: awardCategoryWon Context triple: [Love Serenade, awardCategoryWon, Best First Feature Film at Cannes (Caméra d'Or)]
-
A.
awardReceived
Indicates that an entity has been granted or honored with a specific award or recognition.
-
B.
awardConferred
Indicates that an award or honor has been formally granted by one entity to another.
-
C.
awardReceivedWith
Indicates that an entity received a specific award, optionally together with additional contextual details such as the work, role, or circumstances associated with that award.
-
D.
awardName
Indicates the specific name or title of an award associated with an entity.
-
E.
awardType
chosen
Indicates the specific category or kind of award associated with an entity or event.
- 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_69e0b4bc90988190ac360aaf645efc1d |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6abdf9d7c8190969247a4ae55b781 |
completed | April 20, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69e5a00c43308190b7ea58d559257e07 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:41 a.m.