Triple

T33094045
Position Surface form Disambiguated ID Type / Status
Subject Great Denmark Street E846860 entity
Predicate hasConnectingStreet P36837 FINISHED
Object North Great George’s Street
North Great George’s Street is a historic Georgian residential street in central Dublin, Ireland, noted for its well-preserved 18th-century architecture.
 E2087513 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: North Great George’s Street | Statement: [Great Denmark Street, hasConnectingStreet, North Great George’s 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: North Great George’s Street
Triple: [Great Denmark Street, hasConnectingStreet, North Great George’s Street]
Generated description
North Great George’s Street is a historic Georgian residential street in central Dublin, Ireland, noted for its well-preserved 18th-century architecture.

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_69f3495590dc8190aa04f3dec74ce976 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d6a6b04c8190bee4cf9c00665ef7 completed May 3, 2026, 5:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36d5c2a51081908e0b0eee851dd73a completed June 20, 2026, 6:02 p.m.
NEDg Description generation batch_6a36d6b0c28c81908a5df9c1a0ea3f28 completed June 20, 2026, 6:06 p.m.
NED2 Entity disambiguation (via description) batch_6a36d7f3aee08190990b904cad3029de completed June 20, 2026, 6:12 p.m.
Created at: May 1, 2026, 1:26 a.m.