Triple

T26444468
Position Surface form Disambiguated ID Type / Status
Subject Grand-Place of Ath E665178 entity
Predicate nearbyFeature P2064 FINISHED
Object Église Saint-Julien d'Ath
Église Saint-Julien d'Ath is a historic Roman Catholic church in the Belgian town of Ath, noted for its architectural and cultural significance in the town center.
E1725002 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: Église Saint-Julien d'Ath | Statement: [Grand-Place of Ath, nearbyFeature, Église Saint-Julien d'Ath]
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: Église Saint-Julien d'Ath
Triple: [Grand-Place of Ath, nearbyFeature, Église Saint-Julien d'Ath]
Generated description
Église Saint-Julien d'Ath is a historic Roman Catholic church in the Belgian town of Ath, noted for its architectural and cultural significance in the town center.

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_69ee883c851881909e2ab04efbb3c5fe completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f6121e1f708190902146826b702aab completed May 2, 2026, 3:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11aed165f08190a3d62654e8c23dfb completed May 23, 2026, 1:42 p.m.
NEDg Description generation batch_6a11b06366f48190a0e632695d65ecca completed May 23, 2026, 1:49 p.m.
NED2 Entity disambiguation (via description) batch_6a11b1131e788190bc365f8352fee66a completed May 23, 2026, 1:52 p.m.
Created at: April 27, 2026, 12:01 a.m.