Triple

T23387055
Position Surface form Disambiguated ID Type / Status
Subject The Triumph of Bacchus E593912 entity
Predicate title P38 FINISHED
Object The Triumph of Bacchus
The Triumph of Bacchus is a celebrated Baroque painting by Diego Velázquez depicting the Roman god of wine surrounded by drunken revelers, blending mythological and everyday realism.
E138236 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: The Triumph of Bacchus | Statement: [The Triumph of Bacchus, title, The Triumph of Bacchus]
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: The Triumph of Bacchus
Triple: [The Triumph of Bacchus, title, The Triumph of Bacchus]
Generated description
The Triumph of Bacchus is a celebrated Baroque painting by Diego Velázquez depicting the Roman god of wine surrounded by drunken revelers, blending mythological and everyday realism.

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_69e25d2754fc819085deea939bde60ab completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1a498fd08819085e90a872d9d0c7a completed April 29, 2026, 6:26 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f5372973c8190936351df7e92dc11 completed May 21, 2026, 6:48 p.m.
NEDg Description generation batch_6a0f54d5f37481909f3bf36772aa3493 completed May 21, 2026, 6:54 p.m.
NED2 Entity disambiguation (via description) batch_6a0f55a3a5588190bd6313aacab674a4 completed May 21, 2026, 6:57 p.m.
Created at: April 17, 2026, 5:35 p.m.