Triple
T9519726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cannes Film Festival Award for Best Screenplay |
E229614
|
entity |
| Predicate | hasCeremonyLanguage |
P2769
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Cannes Film Festival Award for Best Screenplay, hasCeremonyLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCeremonyLanguage Context triple: [Cannes Film Festival Award for Best Screenplay, hasCeremonyLanguage, French]
-
A.
languageOfCeremony
chosen
Indicates the language in which a ceremony is conducted or officially performed.
-
B.
hasClericalLanguage
Indicates that something is expressed using formal, religious, or church-related language or terminology.
-
C.
ceremonialLanguageElement
Indicates a linguistic element that is specifically used within or associated with formal ceremonies or ritual contexts.
-
D.
hasLanguageOn
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
-
E.
hasCeremonyBroadcastIn
Indicates that a ceremony is broadcast or transmitted within a specified location or region.
- 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_69ca847870a881909d8d751a7d29da39 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9883c5c48190a6583921afe9730a |
completed | April 1, 2026, 10:13 p.m. |
| PD | Predicate disambiguation | batch_69cca56a3d088190bdc16670678fb6c6 |
completed | April 1, 2026, 4:56 a.m. |
Created at: March 30, 2026, 7:59 p.m.