Triple

T34223306
Position Surface form Disambiguated ID Type / Status
Subject Christchurch Place E877981 entity
Predicate connectsTo P845 FINISHED
Object High Street, Dublin
High Street in Dublin is a historic thoroughfare in the city’s medieval quarter, running through the heart of the old town near landmarks such as Christ Church Cathedral.
E2086502 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: High Street, Dublin | Statement: [Christchurch Place, connectsTo, High Street, Dublin]
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: High Street, Dublin
Triple: [Christchurch Place, connectsTo, High Street, Dublin]
Generated description
High Street in Dublin is a historic thoroughfare in the city’s medieval quarter, running through the heart of the old town near landmarks such as Christ Church Cathedral.

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_69f349b16d0481908754e3069f05e0c1 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f710846ef4819092c9a75057a0d767 completed May 3, 2026, 9:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36cc99137881908eff709440cc0c14 completed June 20, 2026, 5:23 p.m.
NEDg Description generation batch_6a36cd9beb8c81909b8eabf134ea2d17 completed June 20, 2026, 5:27 p.m.
NED2 Entity disambiguation (via description) batch_6a36ce2682d4819082a630dfa1ebc31e completed June 20, 2026, 5:30 p.m.
Created at: May 1, 2026, 1:55 a.m.