Triple

T34051033
Position Surface form Disambiguated ID Type / Status
Subject Everything Waits to Be Noticed E873223 entity
Predicate performer P1363 FINISHED
Object Maia Sharp
Maia Sharp is an American singer-songwriter and producer known for her introspective folk-pop music and collaborations with artists across the adult contemporary and Americana scenes.
E2088452 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: Maia Sharp | Statement: [Everything Waits to Be Noticed, performer, Maia Sharp]
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: Maia Sharp
Triple: [Everything Waits to Be Noticed, performer, Maia Sharp]
Generated description
Maia Sharp is an American singer-songwriter and producer known for her introspective folk-pop music and collaborations with artists across the adult contemporary and Americana scenes.

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_69f349a3ec2c8190b62da76e54231a0f completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f70b67285c8190990a2a219d17e423 completed May 3, 2026, 8:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36d5ccac08819086d61961e064e01a completed June 20, 2026, 6:02 p.m.
NEDg Description generation batch_6a36d6e99b84819097ade5d7eae22c64 completed June 20, 2026, 6:07 p.m.
NED2 Entity disambiguation (via description) batch_6a36d7c18f6c8190be51c8b904b4e6b9 completed June 20, 2026, 6:11 p.m.
Created at: May 1, 2026, 1:51 a.m.