Triple

T28548876
Position Surface form Disambiguated ID Type / Status
Subject This Woman E722823 entity
Predicate hasTrack P3284 FINISHED
Object Nothin’ ’Bout Love Makes Sense
"Nothin’ ’Bout Love Makes Sense" is a country song recorded by LeAnn Rimes, known for its catchy melody and exploration of the confusing nature of love.
E1821999 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: Nothin’ ’Bout Love Makes Sense | Statement: [This Woman, hasTrack, Nothin’ ’Bout Love Makes Sense]
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: Nothin’ ’Bout Love Makes Sense
Triple: [This Woman, hasTrack, Nothin’ ’Bout Love Makes Sense]
Generated description
"Nothin’ ’Bout Love Makes Sense" is a country song recorded by LeAnn Rimes, known for its catchy melody and exploration of the confusing nature of love.

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_69f01a60204481909af1bb76247b8221 completed April 28, 2026, 2:24 a.m.
NER Named-entity recognition batch_69f6500f8ae48190b4f5bd98b505c037 completed May 2, 2026, 7:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cac6dd068819088eab5fd18c6df1e completed May 31, 2026, 9:47 p.m.
NEDg Description generation batch_6a1cad2176088190b0a526811f5c0016 completed May 31, 2026, 9:50 p.m.
NED2 Entity disambiguation (via description) batch_6a1cadf50e1c81908235678a32385afb completed May 31, 2026, 9:53 p.m.
Created at: April 28, 2026, 3:41 a.m.