Triple

T37630095
Position Surface form Disambiguated ID Type / Status
Subject Malta Football Association E936316 entity
Predicate organizesCompetition P527 FINISHED
Object Maltese Women’s League
The Maltese Women’s League is the premier women’s football league in Malta, featuring the country’s top female clubs competing for the national championship.
E2246856 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: Maltese Women’s League | Statement: [Malta Football Association, organizesCompetition, Maltese 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: Maltese Women’s League
Triple: [Malta Football Association, organizesCompetition, Maltese Women’s League]
Generated description
The Maltese Women’s League is the premier women’s football league in Malta, featuring the country’s top female clubs competing for the national championship.

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_69f76ed24820819081bafd36e9088701 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fba959b46c8190aa410c192ba76b63 completed May 6, 2026, 8:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4104070a248190a2cf133105f95882 completed June 28, 2026, 11:22 a.m.
NEDg Description generation batch_6a4104e29abc8190826d9ac7d1dbe4c9 completed June 28, 2026, 11:26 a.m.
NED2 Entity disambiguation (via description) batch_6a4106277e448190bf31165fd8f64020 completed June 28, 2026, 11:31 a.m.
Created at: May 3, 2026, 4:18 p.m.