Triple

T34909752
Position Surface form Disambiguated ID Type / Status
Subject Marvin Macy E1006831 entity
Predicate inLoveWith P7325 FINISHED
Object Miss Amelia Evans
Miss Amelia Evans is a central character in Carson McCullers’ novella "The Ballad of the Sad Café," known as a solitary, strong-willed woman who runs a small-town café and becomes entangled in a tragic love triangle.
E1006829 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: Miss Amelia Evans | Statement: [Marvin Macy, inLoveWith, Miss Amelia Evans]
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: Miss Amelia Evans
Triple: [Marvin Macy, inLoveWith, Miss Amelia Evans]
Generated description
Miss Amelia Evans is a central character in Carson McCullers’ novella "The Ballad of the Sad Café," known as a solitary, strong-willed woman who runs a small-town café and becomes entangled in a tragic love triangle.

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_69f76dc1b4a081909b4c6e4d8ec0aa2d completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7820e2f348190a904bcb407de549e completed May 3, 2026, 5:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37c61ef318819088cce68e7e8418bc completed June 21, 2026, 11:08 a.m.
NEDg Description generation batch_6a37c6e970f48190b35c179e766c58cc completed June 21, 2026, 11:11 a.m.
NED2 Entity disambiguation (via description) batch_6a37cad6f71c81908794928c0e20ab20 completed June 21, 2026, 11:28 a.m.
Created at: May 3, 2026, 4 p.m.