Triple

T29325435
Position Surface form Disambiguated ID Type / Status
Subject Michael Torke E743628 entity
Predicate notableWork P4 FINISHED
Object The Music of Anne Frank
The Music of Anne Frank is a contemporary classical composition by American composer Michael Torke inspired by the life and diary of Anne Frank.
 E1861909 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: The Music of Anne Frank | Statement: [Michael Torke, notableWork, The Music of Anne Frank]
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: The Music of Anne Frank
Triple: [Michael Torke, notableWork, The Music of Anne Frank]
Generated description
The Music of Anne Frank is a contemporary classical composition by American composer Michael Torke inspired by the life and diary of Anne Frank.

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_69f09125f784819080f4e9fce9fe624f completed April 28, 2026, 10:51 a.m.
NER Named-entity recognition batch_69f66895a0d481908efba5930e1ec3b9 completed May 2, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25a87445388190841a05393959b777 completed June 7, 2026, 5:20 p.m.
NEDg Description generation batch_6a25ac6034a081909518662153fbe1b3 completed June 7, 2026, 5:37 p.m.
NED2 Entity disambiguation (via description) batch_6a25b146e9d0819086b956ae8ea30aab completed June 7, 2026, 5:58 p.m.
Created at: April 28, 2026, 1:26 p.m.