Triple

T23863020
Position Surface form Disambiguated ID Type / Status
Subject Den Helder E592500 entity
Predicate hasAttraction P105 FINISHED
Object De Nollen art project and landscape
De Nollen art project and landscape is an open-air art and sculpture park in Den Helder where large-scale works by artist R.W. van de Wint are integrated into a dune landscape.
E1603759 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: De Nollen art project and landscape | Statement: [Den Helder, hasAttraction, De Nollen art project and landscape]
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: De Nollen art project and landscape
Triple: [Den Helder, hasAttraction, De Nollen art project and landscape]
Generated description
De Nollen art project and landscape is an open-air art and sculpture park in Den Helder where large-scale works by artist R.W. van de Wint are integrated into a dune landscape.

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_69e25d22eb488190914b193aff952e83 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1cae16df4819081a8b3a395e45118 completed April 29, 2026, 9:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f69ba28fc81908eff51ddfefd7cda completed May 21, 2026, 8:23 p.m.
NEDg Description generation batch_6a0f6d42f0dc8190a01c02db0e089d68 completed May 21, 2026, 8:38 p.m.
NED2 Entity disambiguation (via description) batch_6a0f6df970a08190b1d3959a39b30233 completed May 21, 2026, 8:41 p.m.
Created at: April 17, 2026, 8:13 p.m.