Triple

T26291997
Position Surface form Disambiguated ID Type / Status
Subject Jürgen Knieper E661299 entity
Predicate notableWork P4 FINISHED
Object Wings of Desire (film score)
Wings of Desire (film score) is the atmospheric, melancholic musical soundtrack composed by Jürgen Knieper for Wim Wenders’ 1987 film "Wings of Desire."
E1717408 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: Wings of Desire (film score) | Statement: [Jürgen Knieper, notableWork, Wings of Desire (film score)]
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: Wings of Desire (film score)
Triple: [Jürgen Knieper, notableWork, Wings of Desire (film score)]
Generated description
Wings of Desire (film score) is the atmospheric, melancholic musical soundtrack composed by Jürgen Knieper for Wim Wenders’ 1987 film "Wings of Desire."

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_69ee812bbd448190be4d7478b057990a completed April 26, 2026, 9:18 p.m.
NER Named-entity recognition batch_69f60eaaac4c8190bcd347bdbe78917e completed May 2, 2026, 2:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a118fc5c3d88190bb2897b63129b9c7 completed May 23, 2026, 11:30 a.m.
NEDg Description generation batch_6a1190d030f08190a8d942eba20a52c4 completed May 23, 2026, 11:34 a.m.
NED2 Entity disambiguation (via description) batch_6a119148a52c8190ab07b136673ee956 completed May 23, 2026, 11:36 a.m.
Created at: April 26, 2026, 10:09 p.m.