Triple

T27862735
Position Surface form Disambiguated ID Type / Status
Subject Israela Margalit E704272 entity
Predicate notableWork P4 FINISHED
Object The Countess
"The Countess" is a stage play by Israela Margalit that dramatizes the turbulent love triangle between art critic John Ruskin, his wife Effie Gray, and painter John Everett Millais in Victorian England.
E1792365 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 Countess | Statement: [Israela Margalit, notableWork, The Countess]
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 Countess
Triple: [Israela Margalit, notableWork, The Countess]
Generated description
"The Countess" is a stage play by Israela Margalit that dramatizes the turbulent love triangle between art critic John Ruskin, his wife Effie Gray, and painter John Everett Millais in Victorian England.

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_69ef840f12408190b539d00d79658abf completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f6394583108190b8f5438a4b4f7211 completed May 2, 2026, 5:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12f744f9cc819092afa08e2724e77e completed May 24, 2026, 1:04 p.m.
NEDg Description generation batch_6a12f7ff676c8190aee03de906240938 completed May 24, 2026, 1:07 p.m.
NED2 Entity disambiguation (via description) batch_6a12fb5822408190812399cb2a623e74 completed May 24, 2026, 1:21 p.m.
Created at: April 27, 2026, 6:19 p.m.