Triple

T33770470
Position Surface form Disambiguated ID Type / Status
Subject Adam Sutler E865364 entity
Predicate occupation P3 FINISHED
Object High Chancellor of Britain
The High Chancellor of Britain is the authoritarian head of government in the dystopian setting of *V for Vendetta*, wielding near-absolute political power over the country.
E2066787 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: High Chancellor of Britain | Statement: [Adam Sutler, occupation, High Chancellor of Britain]
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: High Chancellor of Britain
Triple: [Adam Sutler, occupation, High Chancellor of Britain]
Generated description
The High Chancellor of Britain is the authoritarian head of government in the dystopian setting of *V for Vendetta*, wielding near-absolute political power over the country.

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_69f3498df6f88190bf9647ea4e4a956e completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fc91f488819084fe92081a8bc697 completed May 3, 2026, 7:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36657f2fd88190b998716a713f4730 completed June 20, 2026, 10:03 a.m.
NEDg Description generation batch_6a3665efbb448190922dc19f5096ddeb completed June 20, 2026, 10:05 a.m.
NED2 Entity disambiguation (via description) batch_6a36668c38748190862e1994968ce873 completed June 20, 2026, 10:08 a.m.
Created at: May 1, 2026, 1:45 a.m.