Triple

T27654029
Position Surface form Disambiguated ID Type / Status
Subject Giya Kancheli E696939 entity
Predicate notableWork P4 FINISHED
Object Mourned by the Wind
Mourned by the Wind is a contemplative orchestral work by Georgian composer Giya Kancheli, noted for its stark contrasts, spiritual atmosphere, and meditative use of silence.
E1784128 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: Mourned by the Wind | Statement: [Giya Kancheli, notableWork, Mourned by the Wind]
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: Mourned by the Wind
Triple: [Giya Kancheli, notableWork, Mourned by the Wind]
Generated description
Mourned by the Wind is a contemplative orchestral work by Georgian composer Giya Kancheli, noted for its stark contrasts, spiritual atmosphere, and meditative use of silence.

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_69ef590abd3c8190834d0193bde12007 completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f631d7fa3c8190a5215a730060c895 completed May 2, 2026, 5:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12da99a7088190adae6a011d941654 completed May 24, 2026, 11:01 a.m.
NEDg Description generation batch_6a12db2833688190af921e97c6e5d05d completed May 24, 2026, 11:04 a.m.
NED2 Entity disambiguation (via description) batch_6a12db977df48190b71bce8408b51269 completed May 24, 2026, 11:05 a.m.
Created at: April 27, 2026, 2:33 p.m.