Triple

T37702898
Position Surface form Disambiguated ID Type / Status
Subject Lygia Fagundes Telles E939113 entity
Predicate notableWork P4 FINISHED
Object A Disciplina do Amor
A Disciplina do Amor is a reflective, introspective work by Brazilian writer Lygia Fagundes Telles that blends autobiographical elements, essays, and fiction to explore love, memory, and the craft of writing.
E2239770 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: A Disciplina do Amor | Statement: [Lygia Fagundes Telles, notableWork, A Disciplina do Amor]
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: A Disciplina do Amor
Triple: [Lygia Fagundes Telles, notableWork, A Disciplina do Amor]
Generated description
A Disciplina do Amor is a reflective, introspective work by Brazilian writer Lygia Fagundes Telles that blends autobiographical elements, essays, and fiction to explore love, memory, and the craft of writing.

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_69f76eda6ae48190b3111071eeacc038 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fbae27a4508190a349a9e69c96629e completed May 6, 2026, 9:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40cdc9e86c81908c6474506c338fd8 completed June 28, 2026, 7:31 a.m.
NEDg Description generation batch_6a40ce5899208190bd9ce55470abe0e7 completed June 28, 2026, 7:33 a.m.
NED2 Entity disambiguation (via description) batch_6a40cf3590c48190988529eb57a92a9e completed June 28, 2026, 7:37 a.m.
Created at: May 3, 2026, 4:18 p.m.