Triple

T34465595
Position Surface form Disambiguated ID Type / Status
Subject Dublin city centre cultural quarter E884758 entity
Predicate partOf P40 FINISHED
Object Dublin city centre
Dublin city centre is the compact, historic and commercial heart of Ireland’s capital, known for its dense mix of shopping streets, cultural quarters, nightlife, and major civic landmarks.
E9406 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: Dublin city centre | Statement: [Dublin city centre cultural quarter, partOf, Dublin city centre]
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: Dublin city centre
Triple: [Dublin city centre cultural quarter, partOf, Dublin city centre]
Generated description
Dublin city centre is the compact, historic and commercial heart of Ireland’s capital, known for its dense mix of shopping streets, cultural quarters, nightlife, and major civic landmarks.

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_69f349c73a94819094dfcf50d00620b8 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f71999aec481908c81bc0a9250d7fb completed May 3, 2026, 9:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a37661164e88190bb91b45c0af00c18 completed June 21, 2026, 4:18 a.m.
NEDg Description generation batch_6a3766c62020819090092f8f0de60644 completed June 21, 2026, 4:21 a.m.
NED2 Entity disambiguation (via description) batch_6a37673026e881908b26f42f12f81b2f completed June 21, 2026, 4:23 a.m.
Created at: May 1, 2026, 2:01 a.m.