Triple

T36205325
Position Surface form Disambiguated ID Type / Status
Subject Gandolfi E1047382 entity
Predicate hasNotableBearer P458 FINISHED
Object Michael Gandolfi
Michael Gandolfi is an American contemporary classical composer known for his colorful orchestral works and collaborations with major ensembles and institutions.
E2289445 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: Michael Gandolfi | Statement: [Gandolfi, hasNotableBearer, Michael Gandolfi]
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: Michael Gandolfi
Triple: [Gandolfi, hasNotableBearer, Michael Gandolfi]
Generated description
Michael Gandolfi is an American contemporary classical composer known for his colorful orchestral works and collaborations with major ensembles and institutions.

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_69f76e414bdc8190996f15a544220a3d completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b54e97cc819095abe23e43ec1149 completed May 3, 2026, 8:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5b389ee3e88190b5151b3861be7ccd completed July 18, 2026, 8:26 a.m.
NEDg Description generation batch_6a5b3921c9a48190bd634dfe2ee98dc0 completed July 18, 2026, 8:28 a.m.
NED2 Entity disambiguation (via description) batch_6a5b3972790c81908318a7c287cc81f7 completed July 18, 2026, 8:29 a.m.
Created at: May 3, 2026, 4:08 p.m.