Triple

T28815310
Position Surface form Disambiguated ID Type / Status
Subject Aughagower and Murrisk parish E727624 entity
Predicate hasCommunity P2605 FINISHED
Object Murrisk community
Murrisk community is a small coastal settlement in County Mayo, Ireland, known for its proximity to Croagh Patrick and its strong local parish identity.
E1837260 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: Murrisk community | Statement: [Aughagower and Murrisk parish, hasCommunity, Murrisk community]
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: Murrisk community
Triple: [Aughagower and Murrisk parish, hasCommunity, Murrisk community]
Generated description
Murrisk community is a small coastal settlement in County Mayo, Ireland, known for its proximity to Croagh Patrick and its strong local parish identity.

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_69f0319d09088190bbf14cdf1987792a completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f658f270d88190a183a3eda5c649ff completed May 2, 2026, 8:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24bba11e8c81909b1acbd91f63a950 completed June 7, 2026, 12:30 a.m.
NEDg Description generation batch_6a24c31cbe4481909f83444c8f3c9186 completed June 7, 2026, 1:02 a.m.
NED2 Entity disambiguation (via description) batch_6a24c71493c48190b0cd4152ab76f5e3 completed June 7, 2026, 1:19 a.m.
Created at: April 28, 2026, 6:32 a.m.