Triple

T30292539
Position Surface form Disambiguated ID Type / Status
Subject Charles Square E770417 entity
Predicate hasNearbyLandmark P2064 FINISHED
Object Church of St. Ignatius (Prague)
The Church of St. Ignatius in Prague is a prominent Baroque Jesuit church known for its richly decorated interior and historical significance in the New Town district.
E1908370 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 St. Ignatius (Prague) | Statement: [Charles Square, hasNearbyLandmark, Church of St. Ignatius (Prague)]
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 St. Ignatius (Prague)
Triple: [Charles Square, hasNearbyLandmark, Church of St. Ignatius (Prague)]
Generated description
The Church of St. Ignatius in Prague is a prominent Baroque Jesuit church known for its richly decorated interior and historical significance in the New Town district.

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_69f224875c288190a9b96b975006ec4a completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6813474208190b3e2f0ad7d2b9aab completed May 2, 2026, 10:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a276f06fde481909dc21f19de2c138c completed June 9, 2026, 1:40 a.m.
NEDg Description generation batch_6a27721edee881908602e8a3e48a33f0 completed June 9, 2026, 1:53 a.m.
NED2 Entity disambiguation (via description) batch_6a27727c810c8190a9fff801d64b977f completed June 9, 2026, 1:55 a.m.
Created at: April 29, 2026, 7:47 p.m.