Triple

T36910714
Position Surface form Disambiguated ID Type / Status
Subject Boundary Estate E912897 entity
Predicate replaces P101 FINISHED
Object Old Nichol slum
The Old Nichol slum was a notorious late-19th-century East End London slum, emblematic of extreme urban poverty and overcrowding before its clearance for social housing redevelopment.
 E2205358 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: Old Nichol slum | Statement: [Boundary Estate, replaces, Old Nichol slum]
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: Old Nichol slum
Triple: [Boundary Estate, replaces, Old Nichol slum]
Generated description
The Old Nichol slum was a notorious late-19th-century East End London slum, emblematic of extreme urban poverty and overcrowding before its clearance for social housing redevelopment.

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_69f76e879768819085c2fb31a6a5b44b completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb557f28008190bc684cfb252e0c72 completed May 6, 2026, 2:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e1627fb30819098019fd5660d1158 completed June 26, 2026, 6:03 a.m.
NEDg Description generation batch_6a3e16c7ae008190aed858fd5da64a5d completed June 26, 2026, 6:05 a.m.
NED2 Entity disambiguation (via description) batch_6a3e2225d4fc8190baaf1e61f7e1642f completed June 26, 2026, 6:54 a.m.
Created at: May 3, 2026, 4:13 p.m.