Triple

T25496410
Position Surface form Disambiguated ID Type / Status
Subject Peckham Library E638981 entity
Predicate nearby P350 FINISHED
Object Peckham High Street
Peckham High Street is a bustling main road and commercial hub in the Peckham district of south London, known for its diverse shops, markets, and vibrant street life.
 E1774038 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: Peckham High Street | Statement: [Peckham Library, nearby, Peckham High 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: Peckham High Street
Triple: [Peckham Library, nearby, Peckham High Street]
Generated description
Peckham High Street is a bustling main road and commercial hub in the Peckham district of south London, known for its diverse shops, markets, and vibrant street 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_69e75dbbd2a88190b70e1e645de14b9a completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f7aa25ec819090283c57459555dd completed May 2, 2026, 1:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12bbafcd508190aadd66053104a003 completed May 24, 2026, 8:49 a.m.
NEDg Description generation batch_6a12bc5e92b08190a2a7f60630f6d0ff completed May 24, 2026, 8:52 a.m.
NED2 Entity disambiguation (via description) batch_6a12bcd0c164819098f637afcad01642 completed May 24, 2026, 8:54 a.m.
Created at: April 21, 2026, 2:40 p.m.