Triple

T30077207
Position Surface form Disambiguated ID Type / Status
Subject Fair Phyllis I saw sitting all alone E764352 entity
Predicate character P662 FINISHED
Object Amyntas
Amyntas is a pastoral lover figure in the English madrigal "Fair Phyllis I Saw Sitting All Alone," often portrayed as the shepherd enamored with Phyllis.
E1899875 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: Amyntas | Statement: [Fair Phyllis I saw sitting all alone, character, Amyntas]
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: Amyntas
Triple: [Fair Phyllis I saw sitting all alone, character, Amyntas]
Generated description
Amyntas is a pastoral lover figure in the English madrigal "Fair Phyllis I Saw Sitting All Alone," often portrayed as the shepherd enamored with Phyllis.

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_69f22472eee081909791dc372aa766e9 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67d3eae248190a20399140633dcf7 completed May 2, 2026, 10:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27431e944481909f025d4e2f95f896 completed June 8, 2026, 10:33 p.m.
NEDg Description generation batch_6a2743bb3a8081908e963d8e8f4a9abc completed June 8, 2026, 10:35 p.m.
NED2 Entity disambiguation (via description) batch_6a2744c1a1d881908e1e9a00a065a253 completed June 8, 2026, 10:40 p.m.
Created at: April 29, 2026, 7:02 p.m.