Triple

T32167252
Position Surface form Disambiguated ID Type / Status
Subject Grand Theatre – National Opera, Warsaw E821613 entity
Predicate rebuiltBy P529 FINISHED
Object Bohdan Pniewski
Bohdan Pniewski was a prominent 20th-century Polish architect known for his influential public and monumental buildings in Warsaw.
E2239495 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: Bohdan Pniewski | Statement: [Grand Theatre – National Opera, Warsaw, rebuiltBy, Bohdan Pniewski]
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: Bohdan Pniewski
Triple: [Grand Theatre – National Opera, Warsaw, rebuiltBy, Bohdan Pniewski]
Generated description
Bohdan Pniewski was a prominent 20th-century Polish architect known for his influential public and monumental buildings in Warsaw.

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_69f3490699a48190bbef96b198e8fade completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6ba2089588190808706cc40fea7d6 completed May 3, 2026, 2:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a40cd9a6d788190b234b738c8d7c084 completed June 28, 2026, 7:30 a.m.
NEDg Description generation batch_6a40ce5899208190bd9ce55470abe0e7 completed June 28, 2026, 7:33 a.m.
NED2 Entity disambiguation (via description) batch_6a40cf3590c48190988529eb57a92a9e completed June 28, 2026, 7:37 a.m.
Created at: May 1, 2026, 12:33 a.m.