Triple

T38254644
Position Surface form Disambiguated ID Type / Status
Subject Staunton E1017751 entity
Predicate hasVariant P455 FINISHED
Object Stanton
Stanton is a surname and place name used in various English-speaking regions, often associated with towns, counties, and notable individuals.
E2263090 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: Stanton | Statement: [Staunton, hasVariant, Stanton]
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: Stanton
Triple: [Staunton, hasVariant, Stanton]
Generated description
Stanton is a surname and place name used in various English-speaking regions, often associated with towns, counties, and notable individuals.

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_69f76de33e4481909099fa812709bd42 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fcb1a277688190a265d0b16d6fa236 completed May 7, 2026, 3:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4193d08f1c8190827c8876ce894536 completed June 28, 2026, 9:36 p.m.
NEDg Description generation batch_6a41947a2f608190aba9f20c7e4cd8d6 completed June 28, 2026, 9:39 p.m.
NED2 Entity disambiguation (via description) batch_6a4195210170819086828d7780a6e407 completed June 28, 2026, 9:41 p.m.
Created at: May 3, 2026, 4:30 p.m.