Triple

T29806056
Position Surface form Disambiguated ID Type / Status
Subject The Dreaming E756842 entity
Predicate hasPart P35 FINISHED
Object There Goes a Tenner
"There Goes a Tenner" is a song by English art-pop musician Kate Bush, featured on her 1982 album *The Dreaming* and known for its theatrical narrative about a bungled robbery.
 E1884153 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: There Goes a Tenner | Statement: [The Dreaming, hasPart, There Goes a Tenner]
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: There Goes a Tenner
Triple: [The Dreaming, hasPart, There Goes a Tenner]
Generated description
"There Goes a Tenner" is a song by English art-pop musician Kate Bush, featured on her 1982 album *The Dreaming* and known for its theatrical narrative about a bungled robbery.

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_69f2245584848190ad4cab1f07752ccb completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f6752a26788190a157810a0a585268 completed May 2, 2026, 10:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26c9133a48819083981280b754ae35 completed June 8, 2026, 1:52 p.m.
NEDg Description generation batch_6a26cd2db9bc8190bdbe700f6522ef39 completed June 8, 2026, 2:09 p.m.
NED2 Entity disambiguation (via description) batch_6a26d94836a88190bf71dbdf15a26d71 completed June 8, 2026, 3:01 p.m.
Created at: April 29, 2026, 5:21 p.m.