Triple

T28131819
Position Surface form Disambiguated ID Type / Status
Subject Meadowmount School of Music E711087 entity
Predicate hasFaculty P141 FINISHED
Object Margaret Pardee
Margaret Pardee was an American violinist and renowned pedagogue best known for her long and influential teaching career at the Juilliard School and Meadowmount School of Music.
 E1870729 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: Margaret Pardee | Statement: [Meadowmount School of Music, hasFaculty, Margaret Pardee]
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: Margaret Pardee
Triple: [Meadowmount School of Music, hasFaculty, Margaret Pardee]
Generated description
Margaret Pardee was an American violinist and renowned pedagogue best known for her long and influential teaching career at the Juilliard School and Meadowmount School of Music.

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_69ef9b73bd288190a21ae3d6aa14f386 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f6412b8ddc8190bc95eb63bd865ef7 completed May 2, 2026, 6:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a260bf53d4081908c1bbafd7ddca14d completed June 8, 2026, 12:25 a.m.
NEDg Description generation batch_6a2610d132e08190aae10db1d5971c04 completed June 8, 2026, 12:46 a.m.
NED2 Entity disambiguation (via description) batch_6a26112473cc8190b7dbc83c7390e709 completed June 8, 2026, 12:47 a.m.
Created at: April 27, 2026, 9:23 p.m.