Triple

T29460740
Position Surface form Disambiguated ID Type / Status
Subject Venus, Mars and Cupid E747226 entity
Predicate hasTitle P38 FINISHED
Object Venus, Mars and Cupid
"Venus, Mars and Cupid" is a mythological-themed artwork, most famously depicted in Renaissance painting, showing the Roman goddess of love with the god of war and the god of desire in an intimate, allegorical scene.
E1869960 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: Venus, Mars and Cupid | Statement: [Venus, Mars and Cupid, hasTitle, Venus, Mars and Cupid]
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: Venus, Mars and Cupid
Triple: [Venus, Mars and Cupid, hasTitle, Venus, Mars and Cupid]
Generated description
"Venus, Mars and Cupid" is a mythological-themed artwork, most famously depicted in Renaissance painting, showing the Roman goddess of love with the god of war and the god of desire in an intimate, allegorical scene.

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_69f0bd4125f88190b56104591351619c completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f66ba3925c81909a03f88f1af602b0 completed May 2, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25f10f6b68819099ae50442cb7a098 completed June 7, 2026, 10:30 p.m.
NEDg Description generation batch_6a25f511e960819093280d75cefec6fd completed June 7, 2026, 10:47 p.m.
NED2 Entity disambiguation (via description) batch_6a25f92f6744819093a671170bd83115 completed June 7, 2026, 11:05 p.m.
Created at: April 28, 2026, 3:49 p.m.