Triple

T34223755
Position Surface form Disambiguated ID Type / Status
Subject Meath Street market E877991 entity
Predicate near P350 FINISHED
Object Francis Street, Dublin
Francis Street, Dublin is a historic street in the Liberties area known for its antique shops, art galleries, and proximity to traditional markets and churches.
E2102691 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: Francis Street, Dublin | Statement: [Meath Street market, near, Francis 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: Francis Street, Dublin
Triple: [Meath Street market, near, Francis Street, Dublin]
Generated description
Francis Street, Dublin is a historic street in the Liberties area known for its antique shops, art galleries, and proximity to traditional markets and churches.

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_6a373606cbdc819082aa0b391887fde9 completed June 21, 2026, 12:53 a.m.
NEDg Description generation batch_6a37368f20cc8190890a915e66621f6d completed June 21, 2026, 12:55 a.m.
NED2 Entity disambiguation (via description) batch_6a373711fb94819086195281459bb17e completed June 21, 2026, 12:57 a.m.
Created at: May 1, 2026, 1:55 a.m.