Triple

T27567845
Position Surface form Disambiguated ID Type / Status
Subject Náměšť nad Oslavou E695950 entity
Predicate hasLandmark P105 FINISHED
Object Church of Saint John the Baptist
The Church of Saint John the Baptist is a historic Christian church and notable landmark in the Czech town of Náměšť nad Oslavou.
 E1784610 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: Church of Saint John the Baptist | Statement: [Náměšť nad Oslavou, hasLandmark, Church of Saint John the Baptist]
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: Church of Saint John the Baptist
Triple: [Náměšť nad Oslavou, hasLandmark, Church of Saint John the Baptist]
Generated description
The Church of Saint John the Baptist is a historic Christian church and notable landmark in the Czech town of Náměšť nad Oslavou.

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_69ef53891af88190a193c5e2a1dac9b1 completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62fe9a7748190839d5043d97bd9b2 completed May 2, 2026, 5:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12da7bb3c88190ba2a7d2590a13a50 completed May 24, 2026, 11:01 a.m.
NEDg Description generation batch_6a12db0cb9648190b394ef4009fda2b4 completed May 24, 2026, 11:03 a.m.
NED2 Entity disambiguation (via description) batch_6a12dbf956748190a6763112e384f761 completed May 24, 2026, 11:07 a.m.
Created at: April 27, 2026, 1:42 p.m.