Triple

T32104447
Position Surface form Disambiguated ID Type / Status
Subject You Gotta Pay the Band E819942 entity
Predicate precedes P97 FINISHED
Object Devil's Got Your Tongue
"Devil's Got Your Tongue" is a jazz album by American vocalist Abbey Lincoln, showcasing her distinctive, emotionally charged singing and mature songwriting.
E1991805 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: Devil's Got Your Tongue | Statement: [You Gotta Pay the Band, precedes, Devil's Got Your Tongue]
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: Devil's Got Your Tongue
Triple: [You Gotta Pay the Band, precedes, Devil's Got Your Tongue]
Generated description
"Devil's Got Your Tongue" is a jazz album by American vocalist Abbey Lincoln, showcasing her distinctive, emotionally charged singing and mature songwriting.

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_69f34901106881908ea893ad504a08be completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b698ef508190af74879f83f23fac completed May 3, 2026, 2:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2ede01611c819084e5de74b3857d65 completed June 14, 2026, 4:59 p.m.
NEDg Description generation batch_6a2ede8d1d748190ac4f0ed7ac37ba90 completed June 14, 2026, 5:02 p.m.
NED2 Entity disambiguation (via description) batch_6a2edf2f49048190869080a3d70f4434 completed June 14, 2026, 5:04 p.m.
Created at: May 1, 2026, 12:26 a.m.