Triple

T38667889
Position Surface form Disambiguated ID Type / Status
Subject Helen Simpson E940504 entity
Predicate notableWork P4 FINISHED
Object The Spanish Duchess
"The Spanish Duchess" is a historical novel by Australian-born British writer Helen Simpson, likely exploring aristocratic life and personal drama in a richly detailed European setting.
 E2282459 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 Spanish Duchess | Statement: [Helen Simpson, notableWork, The Spanish Duchess]
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 Spanish Duchess
Triple: [Helen Simpson, notableWork, The Spanish Duchess]
Generated description
"The Spanish Duchess" is a historical novel by Australian-born British writer Helen Simpson, likely exploring aristocratic life and personal drama in a richly detailed European setting.

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_69f76edfde348190bf6529d9f49ecd62 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcdc101ed88190988619025c9350c2 completed May 7, 2026, 6:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a421bd8d16c81909a52cb820d780f6c completed June 29, 2026, 7:16 a.m.
NEDg Description generation batch_6a421d59a34881909e56c35f9809626b completed June 29, 2026, 7:23 a.m.
NED2 Entity disambiguation (via description) batch_6a421dc811c88190b08c7aadb88c478d completed June 29, 2026, 7:24 a.m.
Created at: May 3, 2026, 4:33 p.m.