Triple

T30577903
Position Surface form Disambiguated ID Type / Status
Subject Trafalgar Square conservation area E778299 entity
Predicate hasPart P35 FINISHED
Object Duncannon Street
Duncannon Street is a central London street near Trafalgar Square, known for its historic urban setting and role as a key pedestrian and traffic route in the West End.
 E1972024 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: Duncannon Street | Statement: [Trafalgar Square conservation area, hasPart, Duncannon 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: Duncannon Street
Triple: [Trafalgar Square conservation area, hasPart, Duncannon Street]
Generated description
Duncannon Street is a central London street near Trafalgar Square, known for its historic urban setting and role as a key pedestrian and traffic route in the West End.

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_69f2249f8c148190ae7eb3912cde112a completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6893ee6a081908d04f81d92a0c210 completed May 2, 2026, 11:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2b79ab00d481909a7bf353d5a45492 completed June 12, 2026, 3:14 a.m.
NEDg Description generation batch_6a2b7a866a408190a377ebe1dfb4b162 completed June 12, 2026, 3:18 a.m.
NED2 Entity disambiguation (via description) batch_6a2b7b5699c48190b83c080aa685a7b4 completed June 12, 2026, 3:21 a.m.
Created at: April 29, 2026, 8:23 p.m.