Triple

T25957853
Position Surface form Disambiguated ID Type / Status
Subject Ralph Cudworth E645453 entity
Predicate birthPlace P1 FINISHED
Object Aller, Somerset, England
Aller, Somerset, England is a small rural village and civil parish in the county of Somerset, known for its historic church and traditional West Country landscape.
E1704660 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: Aller, Somerset, England | Statement: [Ralph Cudworth, birthPlace, Aller, Somerset, England]
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: Aller, Somerset, England
Triple: [Ralph Cudworth, birthPlace, Aller, Somerset, England]
Generated description
Aller, Somerset, England is a small rural village and civil parish in the county of Somerset, known for its historic church and traditional West Country landscape.

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_69e77e85efc08190997da7fcf98bd300 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f6049fb3cc8190838f62ac732da3f7 completed May 2, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11077be110819089ea0bab10689c80 completed May 23, 2026, 1:48 a.m.
NEDg Description generation batch_6a1109a47700819082eab631a465c838 completed May 23, 2026, 1:57 a.m.
NED2 Entity disambiguation (via description) batch_6a110a3dc68481909769d05e2c2535bd completed May 23, 2026, 2 a.m.
Created at: April 22, 2026, 8:46 a.m.