Triple

T33788730
Position Surface form Disambiguated ID Type / Status
Subject Tom Dowd & the Language of Music E865869 entity
Predicate director P255 FINISHED
Object Mark Moormann
Mark Moormann is an American documentary filmmaker best known for his music-focused films, including the acclaimed documentary about legendary producer Tom Dowd.
E2066646 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: Mark Moormann | Statement: [Tom Dowd & the Language of Music, director, Mark Moormann]
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: Mark Moormann
Triple: [Tom Dowd & the Language of Music, director, Mark Moormann]
Generated description
Mark Moormann is an American documentary filmmaker best known for his music-focused films, including the acclaimed documentary about legendary producer Tom Dowd.

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_69f3498ecc2c8190bcd85e3f11dc215e completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fcd51fc081908830861c76f0ab30 completed May 3, 2026, 7:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36658f78908190b7dad0b4b07fb617 completed June 20, 2026, 10:03 a.m.
NEDg Description generation batch_6a3665dab17c81908b1c31e64f2e5172 completed June 20, 2026, 10:05 a.m.
NED2 Entity disambiguation (via description) batch_6a366659c0e88190baca08bcc1238f72 completed June 20, 2026, 10:07 a.m.
Created at: May 1, 2026, 1:45 a.m.