Triple
T3782827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juste pour rire |
E85458
|
entity |
| Predicate | significantEventType |
P51476
|
FINISHED |
| Object | comedy gala |
—
|
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 gala | Statement: [Juste pour rire, significantEventType, comedy gala]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: significantEventType Context triple: [Juste pour rire, significantEventType, comedy gala]
-
A.
significantEvent
Indicates that an event involving the entities is of notable importance or impact within a given context.
-
B.
significantEventEnd
Indicates the point in time when a significant event or occurrence comes to a close or is considered finished.
-
C.
significantEventRole
Indicates that an entity plays an important or defining role in a particular significant event.
-
D.
impactEvent
Indicates that one entity physically strikes or collides with another, producing a resulting effect or change.
-
E.
significantPort
Indicates that a port holds major importance in terms of trade, transportation, or strategic relevance within a given context.
- F. None of above. chosen
Provenance (4 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_69aed937fa8881908208ef3801060826 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee634c6ac819099653c660c286746 |
completed | March 9, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69aee3d3c92c819081d9d5c45ef37a5d |
completed | March 9, 2026, 3:14 p.m. |
| PDg | Predicate description generation | batch_69aee633dab88190b14cec8afb19ca6a |
completed | March 9, 2026, 3:24 p.m. |
Created at: March 9, 2026, 3:13 p.m.