Triple

T26561635
Position Surface form Disambiguated ID Type / Status
Subject Terschelling E666257 entity
Predicate hasEvent P811 FINISHED
Object Oerol Festival
Oerol Festival is a renowned annual Dutch cultural and performing arts festival that transforms the island of Terschelling into an open-air stage for theater, music, and site-specific art.
E1733028 NE 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: Oerol Festival | Statement: [Terschelling, hasEvent, Oerol Festival]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Oerol Festival
Triple: [Terschelling, hasEvent, Oerol Festival]
Generated description
Oerol Festival is a renowned annual Dutch cultural and performing arts festival that transforms the island of Terschelling into an open-air stage for theater, music, and site-specific art.

Provenance (5 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_69ee9cf7e94481909f0d556b36e43572 completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f6146c6e188190aa022ef2b9ee1774 completed May 2, 2026, 3:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11c825fc2481909a95ac8b29dacea6 completed May 23, 2026, 3:30 p.m.
NEDg Description generation batch_6a11c945273c8190ac0bc6fe508a6d9a completed May 23, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_6a11ca68b0488190851b0634a0c784bd completed May 23, 2026, 3:40 p.m.
Created at: April 27, 2026, 1:53 a.m.