Triple
T3277893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cannes Golden Camera Special Mention |
E68800
|
entity |
| Predicate | relationToMainPrize |
P10713
|
FINISHED |
| Object | does not win the main Caméra d'Or prize |
—
|
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: does not win the main Caméra d'Or prize | Statement: [Cannes Golden Camera Special Mention, relationToMainPrize, does not win the main Caméra d'Or prize]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationToMainPrize Context triple: [Cannes Golden Camera Special Mention, relationToMainPrize, does not win the main Caméra d'Or prize]
-
A.
grantedAsRewardFor
Indicates that something is given to an entity specifically as a reward for a particular action, achievement, or service.
-
B.
hasRelativeWithAward
Indicates that one entity has a relative who has received an award.
-
C.
prizeType
Indicates the specific category or kind of prize associated with an entity or event.
-
D.
prizeContext
chosen
Indicates the situational or contextual circumstances under which a prize is awarded, considered, or relevant.
-
E.
relatedAward
Indicates that there is an award connected or associated with the subject entity, such as an honor, prize, or recognition related to it.
- 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_69ad859c463481909ca4be267336c290 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb013de048190bcaac732caa6b174 |
completed | March 8, 2026, 5:21 p.m. |
| PD | Predicate disambiguation | batch_69ada420167c81909b6e2702db296d9e |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:10 p.m.