Triple
T54353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World Cafe Live |
E1070
|
entity |
| Predicate | audienceType |
P793
|
FINISHED |
| Object | all ages events |
—
|
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: all ages events | Statement: [World Cafe Live, audienceType, all ages events]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: audienceType Context triple: [World Cafe Live, audienceType, all ages events]
-
A.
hasAudience
chosen
Indicates that an entity is intended to be received, viewed, or engaged with by a particular group of people.
-
B.
typeOfSupport
Indicates the kind or category of assistance, help, or backing provided in a given context.
-
C.
programType
Indicates the category or kind of program to which an entity belongs or with which it is associated.
-
D.
customerType
Indicates the classification or category assigned to a customer based on their characteristics, status, or relationship with a business.
-
E.
standardType
Indicates that one entity is classified as the standard, canonical, or reference type for another entity or context.
- 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_69a248adc5b48190aa8db9fb092fb28a |
completed | Feb. 28, 2026, 1:45 a.m. |
| NER | Named-entity recognition | batch_69a24b3a9e848190b80de3c858678b3a |
completed | Feb. 28, 2026, 1:56 a.m. |
| PD | Predicate disambiguation | batch_69a24ac52fb08190aa7c38f83434f795 |
completed | Feb. 28, 2026, 1:54 a.m. |
Created at: Feb. 28, 2026, 1:50 a.m.