Triple

T23796435
Position Surface form Disambiguated ID Type / Status
Subject De Kunstlinie Theater and Cultural Center E588553 entity
Predicate shortName P43 FINISHED
Object De Kunstlinie
De Kunstlinie is a prominent theater and cultural center in Almere, the Netherlands, known for hosting a wide range of performing arts, exhibitions, and community events.
E1600883 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 Kunstlinie | Statement: [De Kunstlinie Theater and Cultural Center, shortName, De Kunstlinie]
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 Kunstlinie
Triple: [De Kunstlinie Theater and Cultural Center, shortName, De Kunstlinie]
Generated description
De Kunstlinie is a prominent theater and cultural center in Almere, the Netherlands, known for hosting a wide range of performing arts, exhibitions, and community events.

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_69e25d15db58819092ac1e6791696fd9 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1c6dc94d481908800385a58d2c452 completed April 29, 2026, 8:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f53f346e08190adb7e1af0f2ca21e completed May 21, 2026, 6:50 p.m.
NEDg Description generation batch_6a0f5634499c8190ac46621942ed2fd3 completed May 21, 2026, 7 p.m.
NED2 Entity disambiguation (via description) batch_6a0f56b2407c8190aa957702cf33267c completed May 21, 2026, 7:02 p.m.
Created at: April 17, 2026, 7:48 p.m.