Triple

T28306351
Position Surface form Disambiguated ID Type / Status
Subject H.E.R. E713860 entity
Predicate notableWork P4 FINISHED
Object “Focus”
“Focus” is a soulful R&B song by H.E.R. known for its minimalist production and introspective lyrics about emotional neglect in a relationship.
E1812133 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: “Focus” | Statement: [H.E.R., notableWork, “Focus”]
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: “Focus”
Triple: [H.E.R., notableWork, “Focus”]
Generated description
“Focus” is a soulful R&B song by H.E.R. known for its minimalist production and introspective lyrics about emotional neglect in a relationship.

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_69efb5256afc8190b9322d25c3ae6320 completed April 27, 2026, 7:12 p.m.
NER Named-entity recognition batch_69f644b6b558819095c70a2eb49f1853 completed May 2, 2026, 6:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a160738dc58819092204bb6841431e7 completed May 26, 2026, 8:48 p.m.
NEDg Description generation batch_6a161433b69c81909fdd10b625bcfb9d completed May 26, 2026, 9:44 p.m.
NED2 Entity disambiguation (via description) batch_6a1614a18c3c8190b9eb9f87149201df completed May 26, 2026, 9:46 p.m.
Created at: April 27, 2026, 11:38 p.m.