Triple

T24332549
Position Surface form Disambiguated ID Type / Status
Subject Talk to Me E613285 entity
Predicate composer P1361 FINISHED
Object Liza Richardson
Liza Richardson is an American music supervisor and DJ known for curating influential soundtracks for film and television.
E1686937 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: Liza Richardson | Statement: [Talk to Me, composer, Liza Richardson]
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: Liza Richardson
Triple: [Talk to Me, composer, Liza Richardson]
Generated description
Liza Richardson is an American music supervisor and DJ known for curating influential soundtracks for film and television.

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_69e2d7db6d5c819091194918157a7c1f completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f292f23db08190b701bb13aef7f10d completed April 29, 2026, 11:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10b6fca5ec8190b279806d28814da2 completed May 22, 2026, 8:05 p.m.
NEDg Description generation batch_6a10b7fa6d60819097ff930865af4032 completed May 22, 2026, 8:09 p.m.
NED2 Entity disambiguation (via description) batch_6a10b9651af481909206495b2fc57a2e completed May 22, 2026, 8:15 p.m.
Created at: April 18, 2026, 1:56 a.m.