Triple

T36249072
Position Surface form Disambiguated ID Type / Status
Subject Théodore Chassériau E891744 entity
Predicate notableWork P4 FINISHED
Object The Tepidarium
The Tepidarium is a celebrated 1853 painting by French Romantic artist Théodore Chassériau depicting sensuous women in a Roman bath, noted for its exoticism, rich color, and blend of classical and romantic styles.
E2174724 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 Tepidarium | Statement: [Théodore Chassériau, notableWork, The Tepidarium]
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 Tepidarium
Triple: [Théodore Chassériau, notableWork, The Tepidarium]
Generated description
The Tepidarium is a celebrated 1853 painting by French Romantic artist Théodore Chassériau depicting sensuous women in a Roman bath, noted for its exoticism, rich color, and blend of classical and romantic styles.

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_69f76e4599108190811532e707d6bc2c completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b5f89c5c8190825ed5d4317c540c completed May 3, 2026, 8:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a394d4a5bac8190954461bb396e1289 completed June 22, 2026, 2:57 p.m.
NEDg Description generation batch_6a394f0c50f88190a119bae5ad7af076 completed June 22, 2026, 3:04 p.m.
NED2 Entity disambiguation (via description) batch_6a39514c8b688190be3f7f8b911d0b35 completed June 22, 2026, 3:14 p.m.
Created at: May 3, 2026, 4:09 p.m.