Triple

T28331829
Position Surface form Disambiguated ID Type / Status
Subject La jolie fille de Perth E717555 entity
Predicate vocalTypeOfCharacter P135747 FINISHED
Object Duke of Rothsay – tenor
Duke of Rothsay – tenor is the principal tenor role in Bizet’s opera "La jolie fille de Perth," portraying the romantic nobleman at the center of the drama.
 E1813595 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: Duke of Rothsay – tenor | Statement: [La jolie fille de Perth, vocalTypeOfCharacter, Duke of Rothsay – tenor]
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: Duke of Rothsay – tenor
Triple: [La jolie fille de Perth, vocalTypeOfCharacter, Duke of Rothsay – tenor]
Generated description
Duke of Rothsay – tenor is the principal tenor role in Bizet’s opera "La jolie fille de Perth," portraying the romantic nobleman at the center of the drama.

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_69eff6e9a57c8190a69c2c74b5d72119 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f68b7fadd88190a17b92b09ddb6f11 completed May 2, 2026, 11:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1627b7149481908457a97233ccfa45 completed May 26, 2026, 11:07 p.m.
NEDg Description generation batch_6a16294860f08190adf72188a0fe0c18 completed May 26, 2026, 11:14 p.m.
NED2 Entity disambiguation (via description) batch_6a162a96c8c48190a4987d51fa9ea9ee completed May 26, 2026, 11:19 p.m.
Created at: April 28, 2026, 12:32 a.m.