Triple

T25478211
Position Surface form Disambiguated ID Type / Status
Subject Grote Markt (Veurne) E638491 entity
Predicate hasView P854 FINISHED
Object Saint Walburga Church tower
The Saint Walburga Church tower is a prominent historic church tower in Veurne, Belgium, known for its striking Gothic architecture and its role as a key landmark overlooking the town’s central square.
E1678840 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: Saint Walburga Church tower | Statement: [Grote Markt (Veurne), hasView, Saint Walburga Church tower]
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: Saint Walburga Church tower
Triple: [Grote Markt (Veurne), hasView, Saint Walburga Church tower]
Generated description
The Saint Walburga Church tower is a prominent historic church tower in Veurne, Belgium, known for its striking Gothic architecture and its role as a key landmark overlooking the town’s central square.

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_69e75db9b964819096802dcf502e577e completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f7737a1c81909933c73eacdfd6a8 completed May 2, 2026, 1:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1089c103e08190bc070fe0a69ed905 completed May 22, 2026, 4:52 p.m.
NEDg Description generation batch_6a108a67fc908190926977f4e65dba0b completed May 22, 2026, 4:55 p.m.
NED2 Entity disambiguation (via description) batch_6a108b00aee0819088928d399c5e52b7 completed May 22, 2026, 4:57 p.m.
Created at: April 21, 2026, 2:26 p.m.