Triple
T5145580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eurochocolate |
E116060
|
entity |
| Predicate | relatedEventType |
P38977
|
FINISHED |
| Object | food festival |
—
|
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: food festival | Statement: [Eurochocolate, relatedEventType, food festival]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedEventType Context triple: [Eurochocolate, relatedEventType, food festival]
-
A.
associatedEventType
chosen
Indicates that one entity is linked to another by the type or category of event with which it is associated.
-
B.
relatedType
Indicates that one entity is connected to another through a specified type or category of relationship.
-
C.
laterRelatedEvent
Indicates that one event is temporally related to another by occurring at a later time.
-
D.
relatedTo
Indicates a general, non-specific relationship or association exists between two entities.
-
E.
typicalEvent
Indicates that the associated event is a common, characteristic, or prototypical occurrence for the given entity or situation.
- 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_69bd4446c0e08190a7c29dc74976bf03 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd78d7f4d081908d59adcd86f52f1d |
completed | March 20, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69bd77ae2f10819098bb8939106e1281 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:43 p.m.