Triple

T34244258
Position Surface form Disambiguated ID Type / Status
Subject River Liffey quays E878552 entity
Predicate hasPart P35 FINISHED
Object Merchant's Quay
Merchant's Quay is a historic riverside quay and street along the River Liffey in central Dublin, Ireland, known for its proximity to key civic and religious landmarks.
E2095589 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: Merchant's Quay | Statement: [River Liffey quays, hasPart, Merchant's Quay]
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: Merchant's Quay
Triple: [River Liffey quays, hasPart, Merchant's Quay]
Generated description
Merchant's Quay is a historic riverside quay and street along the River Liffey in central Dublin, Ireland, known for its proximity to key civic and religious 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_69f349b3618481909df955b063f305b2 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f71280ea0c81908508c0cd67f87413 completed May 3, 2026, 9:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a370da9b22c81908d863abbc0e47a15 completed June 20, 2026, 10:01 p.m.
NEDg Description generation batch_6a370e7dcd88819091a402e550189e46 completed June 20, 2026, 10:04 p.m.
NED2 Entity disambiguation (via description) batch_6a370f28a640819080ccc586b22bd785 completed June 20, 2026, 10:07 p.m.
Created at: May 1, 2026, 1:56 a.m.