Triple
T12284864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margarita |
E292802
|
entity |
| Predicate | popularOccasion |
P76573
|
FINISHED |
| Object | summer |
—
|
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: summer | Statement: [Margarita, popularOccasion, summer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: popularOccasion Context triple: [Margarita, popularOccasion, summer]
-
A.
primaryOccasion
Indicates that one occasion is the main or most significant event associated with a given context, entity, or activity.
-
B.
specialOccasion
Indicates that an event or situation is associated with a notable or exceptional occasion, such as a celebration, milestone, or culturally significant date.
-
C.
displayOccasion
Indicates the event, context, or situation during which something is presented, shown, or made visible.
-
D.
occasionType
Indicates the specific kind or category of occasion or event associated with the subject.
-
E.
suitableOccasion
chosen
Indicates that a particular occasion or context is appropriate or fitting for a given entity, action, 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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9261e1570819084bb4fdb44aa6aea |
completed | April 10, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69d91c4d9a9c8190aeb7beaf9792d8f0 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:52 p.m.