Triple

T27700458
Position Surface form Disambiguated ID Type / Status
Subject York Assizes E698413 entity
Predicate jurisdiction P82 FINISHED
Object Northern Circuit
The Northern Circuit is one of the historic English judicial circuits covering the northern counties, where senior judges traveled to hear serious criminal and civil cases.
E1785543 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: Northern Circuit | Statement: [York Assizes, jurisdiction, Northern Circuit]
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: Northern Circuit
Triple: [York Assizes, jurisdiction, Northern Circuit]
Generated description
The Northern Circuit is one of the historic English judicial circuits covering the northern counties, where senior judges traveled to hear serious criminal and civil cases.

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_69ef590ea74081908f0cd7500d85fa27 completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f635a29ff08190bfd246ccaf0ddb4e completed May 2, 2026, 5:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12e456fdb08190972cc8c2cfcdace0 completed May 24, 2026, 11:43 a.m.
NEDg Description generation batch_6a12e51506ac8190bc8cac0bad87dad5 completed May 24, 2026, 11:46 a.m.
NED2 Entity disambiguation (via description) batch_6a12e5e1eafc8190912e291b91690548 completed May 24, 2026, 11:49 a.m.
Created at: April 27, 2026, 2:56 p.m.