Triple

T37336547
Position Surface form Disambiguated ID Type / Status
Subject Christopher Palmer E926906 entity
Predicate notableWork P4 FINISHED
Object The Composer in Hollywood
The Composer in Hollywood is a book by Christopher Palmer that explores the history, craft, and major figures of film music in the American movie industry.
 E2222663 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 Composer in Hollywood | Statement: [Christopher Palmer, notableWork, The Composer in Hollywood]
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 Composer in Hollywood
Triple: [Christopher Palmer, notableWork, The Composer in Hollywood]
Generated description
The Composer in Hollywood is a book by Christopher Palmer that explores the history, craft, and major figures of film music in the American movie industry.

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_69f76eb4e8a881908bd40da28f36fc7e completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb5b6f4aa08190ae9651544f39a725 completed May 6, 2026, 3:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4063a7af1c8190ab08be824cc1adcd completed June 27, 2026, 11:58 p.m.
NEDg Description generation batch_6a40651199688190885c70a183f42565 completed June 28, 2026, 12:04 a.m.
NED2 Entity disambiguation (via description) batch_6a4065d22b248190aa130d1b096d6a60 completed June 28, 2026, 12:07 a.m.
Created at: May 3, 2026, 4:16 p.m.