Triple

T28778531
Position Surface form Disambiguated ID Type / Status
Subject Burrington Combe E726607 entity
Predicate hasViewpoint P854 FINISHED
Object Black Down area
The Black Down area is a high, open expanse of heathland and moor on the Mendip Hills in Somerset, England, known for its panoramic views and relatively unspoiled natural landscape.
E1834909 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: Black Down area | Statement: [Burrington Combe, hasViewpoint, Black Down area]
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: Black Down area
Triple: [Burrington Combe, hasViewpoint, Black Down area]
Generated description
The Black Down area is a high, open expanse of heathland and moor on the Mendip Hills in Somerset, England, known for its panoramic views and relatively unspoiled natural 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_69f03199997c8190b6ae43fb19312443 completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f6584b0f148190892a2566287913ca completed May 2, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24a26b0f9881909e0ff313d3620174 completed June 6, 2026, 10:42 p.m.
NEDg Description generation batch_6a24a638e30881908d94bc85bfb4b3a4 completed June 6, 2026, 10:59 p.m.
NED2 Entity disambiguation (via description) batch_6a24b191b75c8190842a72cd498304fe completed June 6, 2026, 11:47 p.m.
Created at: April 28, 2026, 6:18 a.m.