Triple

T28768381
Position Surface form Disambiguated ID Type / Status
Subject Coyote Ugly: Original Motion Picture Soundtrack E726339 entity
Predicate performer P1363 FINISHED
Object Tamara Walker
Tamara Walker is an American country and pop singer known for her contributions to film soundtracks and early-2000s contemporary country music.
E1850182 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: Tamara Walker | Statement: [Coyote Ugly: Original Motion Picture Soundtrack, performer, Tamara Walker]
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: Tamara Walker
Triple: [Coyote Ugly: Original Motion Picture Soundtrack, performer, Tamara Walker]
Generated description
Tamara Walker is an American country and pop singer known for her contributions to film soundtracks and early-2000s contemporary country music.

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_69f03198be14819098fa74e48b3749bf completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f65825ace48190ba64bdc631af5e67 completed May 2, 2026, 8:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25378bdb8c81908a1e9a0c0d87b211 completed June 7, 2026, 9:19 a.m.
NEDg Description generation batch_6a253bbd62288190b2cc1a79051748a7 completed June 7, 2026, 9:37 a.m.
NED2 Entity disambiguation (via description) batch_6a253f918e1081909cc569d20fa9bf35 completed June 7, 2026, 9:53 a.m.
Created at: April 28, 2026, 6:14 a.m.