Triple

T35744246
Position Surface form Disambiguated ID Type / Status
Subject Ballina Town F.C. E1033124 entity
Predicate governingBody P46 FINISHED
Object Mayo Football League
The Mayo Football League is the regional governing body that organizes and oversees association football competitions and clubs within County Mayo, Ireland.
E2152916 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: Mayo Football League | Statement: [Ballina Town F.C., governingBody, Mayo Football League]
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: Mayo Football League
Triple: [Ballina Town F.C., governingBody, Mayo Football League]
Generated description
The Mayo Football League is the regional governing body that organizes and oversees association football competitions and clubs within County Mayo, Ireland.

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_69f76e119d508190a3873cb302063832 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a16df2808190bd9dc510537b7fbf completed May 3, 2026, 7:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a387d28e7348190a209cbd52fc5403a completed June 22, 2026, 12:09 a.m.
NEDg Description generation batch_6a387db776108190be2cd974327d0a42 completed June 22, 2026, 12:11 a.m.
NED2 Entity disambiguation (via description) batch_6a387ea615a881909ab9f8e261a2d2f7 completed June 22, 2026, 12:15 a.m.
Created at: May 3, 2026, 4:06 p.m.