Triple

T29647026
Position Surface form Disambiguated ID Type / Status
Subject Baby E756028 entity
Predicate writer P1360 FINISHED
Object Trina Broussard
Trina Broussard is an American R&B and soul singer-songwriter known for her smooth vocals and emotive, jazz-influenced style.
E1877561 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: Trina Broussard | Statement: [Baby, writer, Trina Broussard]
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: Trina Broussard
Triple: [Baby, writer, Trina Broussard]
Generated description
Trina Broussard is an American R&B and soul singer-songwriter known for her smooth vocals and emotive, jazz-influenced style.

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_69f0ef89d2c88190a6d0d5116ccd7cc9 completed April 28, 2026, 5:34 p.m.
NER Named-entity recognition batch_69f66ed3d37c81909b3e973fb9dd70cc completed May 2, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2661839b1c8190bd2cbcf8a7e4c145 completed June 8, 2026, 6:30 a.m.
NEDg Description generation batch_6a266c87573881908d19adc321c6026f completed June 8, 2026, 7:17 a.m.
NED2 Entity disambiguation (via description) batch_6a26706cf20c81909d38339f175f3c81 completed June 8, 2026, 7:34 a.m.
Created at: April 28, 2026, 6:50 p.m.