Triple

T35777451
Position Surface form Disambiguated ID Type / Status
Subject Portman Estate area of London E1034334 entity
Predicate hasPart P35 FINISHED
Object George Street
George Street is a notable thoroughfare in central London’s Marylebone district, known for its mix of historic architecture, residential buildings, and commercial premises.
 E750045 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: George Street | Statement: [Portman Estate area of London, hasPart, George Street]
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: George Street
Triple: [Portman Estate area of London, hasPart, George Street]
Generated description
George Street is a notable thoroughfare in central London’s Marylebone district, known for its mix of historic architecture, residential buildings, and commercial premises.

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_69f76e14a1e081908eddd57bd6fdb3be completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a1fd19a88190968cb8775212e3ac completed May 3, 2026, 7:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3886079c088190808704e3dd2877f2 completed June 22, 2026, 12:47 a.m.
NEDg Description generation batch_6a3887079b888190b35993aa0aa2e1e2 completed June 22, 2026, 12:51 a.m.
NED2 Entity disambiguation (via description) batch_6a38879e7d6c8190b6f7269df6c5d5e1 completed June 22, 2026, 12:53 a.m.
Created at: May 3, 2026, 4:06 p.m.