Triple

T29127816
Position Surface form Disambiguated ID Type / Status
Subject Upper Duke Street E738281 entity
Predicate connectsTo P845 FINISHED
Object Great George Street, Liverpool
Great George Street in Liverpool is a central thoroughfare near the city’s historic core, known for its proximity to landmarks such as the Anglican Cathedral and its mix of residential, commercial, and cultural buildings.
 E1857208 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: Great George Street, Liverpool | Statement: [Upper Duke Street, connectsTo, Great George Street, Liverpool]
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: Great George Street, Liverpool
Triple: [Upper Duke Street, connectsTo, Great George Street, Liverpool]
Generated description
Great George Street in Liverpool is a central thoroughfare near the city’s historic core, known for its proximity to landmarks such as the Anglican Cathedral and its mix of residential, commercial, and cultural buildings.

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_69f07cb29cdc8190afa55444553de60c completed April 28, 2026, 9:24 a.m.
NER Named-entity recognition batch_69f6622b76d481909dfcad6d272e74f0 completed May 2, 2026, 8:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2569aa6718819086862149d51173b6 completed June 7, 2026, 12:52 p.m.
NEDg Description generation batch_6a25749efd7c8190aad9ffde8b82c7c8 completed June 7, 2026, 1:39 p.m.
NED2 Entity disambiguation (via description) batch_6a2578b1705c819080cad536b55277ec completed June 7, 2026, 1:57 p.m.
Created at: April 28, 2026, 11:29 a.m.