Triple

T23614717
Position Surface form Disambiguated ID Type / Status
Subject Slow E583142 entity
Predicate followedBySingle P134 FINISHED
Object Red Blooded Woman
"Red Blooded Woman" is a 2004 dance-pop single by Australian singer Kylie Minogue, known for its catchy hook and sultry, R&B-influenced production.
 E1594657 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: Red Blooded Woman | Statement: [Slow, followedBySingle, Red Blooded Woman]
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: Red Blooded Woman
Triple: [Slow, followedBySingle, Red Blooded Woman]
Generated description
"Red Blooded Woman" is a 2004 dance-pop single by Australian singer Kylie Minogue, known for its catchy hook and sultry, R&B-influenced production.

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_69e248fbcd9081908ba08913f9d30826 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b0f71a2481909c3d0d8d0d58e20f completed April 29, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f459212a0819082040a8d43a8af85 completed May 21, 2026, 5:49 p.m.
NEDg Description generation batch_6a0f46d684b481908baeb3ef405e2833 completed May 21, 2026, 5:54 p.m.
NED2 Entity disambiguation (via description) batch_6a0f47b410e8819093c7578df50bd669 completed May 21, 2026, 5:58 p.m.
Created at: April 17, 2026, 6:45 p.m.