Triple

T29528284
Position Surface form Disambiguated ID Type / Status
Subject The Maiden’s Prayer E749126 entity
Predicate composer P1361 FINISHED
Object Tekla Bądarzewska-Baranowska
Tekla Bądarzewska-Baranowska was a 19th-century Polish composer and pianist best known for her sentimental salon piece "The Maiden’s Prayer."
E1871056 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: Tekla Bądarzewska-Baranowska | Statement: [The Maiden’s Prayer, composer, Tekla Bądarzewska-Baranowska]
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: Tekla Bądarzewska-Baranowska
Triple: [The Maiden’s Prayer, composer, Tekla Bądarzewska-Baranowska]
Generated description
Tekla Bądarzewska-Baranowska was a 19th-century Polish composer and pianist best known for her sentimental salon piece "The Maiden’s Prayer."

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_69f0bd46d99c81908ba9d01cc1dbef7d completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f66c9efdfc8190b2137dc6e1685baf completed May 2, 2026, 9:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a260c320fa48190998217bb23e66669 completed June 8, 2026, 12:26 a.m.
NEDg Description generation batch_6a26101eb69481909e5a27c1fd3791f0 completed June 8, 2026, 12:43 a.m.
NED2 Entity disambiguation (via description) batch_6a26142129608190b8028efd1baf9f50 completed June 8, 2026, 1 a.m.
Created at: April 28, 2026, 4:49 p.m.