Triple
T275356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nantucket Film Festival |
E5234
|
entity |
| Predicate | eventType |
P7504
|
FINISHED |
| Object | cultural 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: cultural festival | Statement: [Nantucket Film Festival, eventType, cultural festival]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eventType Context triple: [Nantucket Film Festival, eventType, cultural festival]
-
A.
event
Indicates that there exists an occurrence or happening involving one or more entities, typically situated in time and possibly space.
-
B.
typeOfEvent
chosen
Indicates that one entity is classified as a specific kind or category of event.
-
C.
typicalEvent
Indicates that the associated event is a common, characteristic, or prototypical occurrence for the given entity or situation.
-
D.
featuresEvent
Indicates that an entity includes, presents, or highlights a particular event as part of its content or offering.
-
E.
eventRole
Indicates the specific function, capacity, or part an entity plays within an event or occurrence.
- 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25dd1cdf881909c2c9b77b7f88684 |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b7480e881909399beccfc7ffb81 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.