Triple

T24318482
Position Surface form Disambiguated ID Type / Status
Subject FAW Women's Cup E612887 entity
Predicate relatedTo P37 FINISHED
Object Welsh Premier Women's League
The Welsh Premier Women's League is the top tier of women's football in Wales, featuring the country's leading clubs competing for the national championship and European qualification.
E1629817 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: Welsh Premier Women's League | Statement: [FAW Women's Cup, relatedTo, Welsh Premier Women's 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: Welsh Premier Women's League
Triple: [FAW Women's Cup, relatedTo, Welsh Premier Women's League]
Generated description
The Welsh Premier Women's League is the top tier of women's football in Wales, featuring the country's leading clubs competing for the national championship and European qualification.

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_69e2d7da491c8190b6e6218af50923db completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f292a916c8819096d018e7ffaf483b completed April 29, 2026, 11:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fc9e213dc8190ad9a56715b74bc35 completed May 22, 2026, 3:13 a.m.
NEDg Description generation batch_6a0fcecc34808190b1b853c9c471a382 completed May 22, 2026, 3:34 a.m.
NED2 Entity disambiguation (via description) batch_6a0fcf5008e08190b0744a9be634cedb completed May 22, 2026, 3:36 a.m.
Created at: April 18, 2026, 1:47 a.m.