Triple

T21899870
Position Surface form Disambiguated ID Type / Status
Subject Mark Sway E540779 entity
Predicate hasRelative P367 FINISHED
Object Dianne Sway
Dianne Sway is a fictional character in John Grisham's novel "The Client," known as the mother of the young protagonist Mark Sway.
E1650139 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: Dianne Sway | Statement: [Mark Sway, hasRelative, Dianne Sway]
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: Dianne Sway
Triple: [Mark Sway, hasRelative, Dianne Sway]
Generated description
Dianne Sway is a fictional character in John Grisham's novel "The Client," known as the mother of the young protagonist Mark Sway.

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_69e0c47b4e8c81908c8076eaa4c8e4f2 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f11fca2bf88190b2a5b912aa102513 completed April 28, 2026, 8:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a101bc2eb5c81909d04175cedf584ad completed May 22, 2026, 9:02 a.m.
NEDg Description generation batch_6a1024c2ab90819085e42e42b48905ce completed May 22, 2026, 9:41 a.m.
NED2 Entity disambiguation (via description) batch_6a10252c2cf48190a31fd50058a5b288 completed May 22, 2026, 9:43 a.m.
Created at: April 16, 2026, 7:07 p.m.