Triple

T35166138
Position Surface form Disambiguated ID Type / Status
Subject New Street, Birmingham E1015407 entity
Predicate hasHeritageBuilding P1098 FINISHED
Object The Burlington Hotel, Birmingham
The Burlington Hotel in Birmingham is a historic, grand Victorian hotel in the city centre, known for its elegant architecture and long-standing role in the city’s social and commercial life.
E2127417 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: The Burlington Hotel, Birmingham | Statement: [New Street, Birmingham, hasHeritageBuilding, The Burlington Hotel, Birmingham]
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: The Burlington Hotel, Birmingham
Triple: [New Street, Birmingham, hasHeritageBuilding, The Burlington Hotel, Birmingham]
Generated description
The Burlington Hotel in Birmingham is a historic, grand Victorian hotel in the city centre, known for its elegant architecture and long-standing role in the city’s social and commercial life.

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_69f76ddbfde081908bffc91572368289 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78d34109c8190acd2299e5f73fd1a completed May 3, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37d96f73848190a28182590c056499 completed June 21, 2026, 12:30 p.m.
NEDg Description generation batch_6a37dbce092c81908ded9e525a778907 completed June 21, 2026, 12:40 p.m.
NED2 Entity disambiguation (via description) batch_6a37dc0c0a5081908ce1002b7181b433 completed June 21, 2026, 12:41 p.m.
Created at: May 3, 2026, 4:02 p.m.