Triple

T30682233
Position Surface form Disambiguated ID Type / Status
Subject 2016–17 UEFA Europa League E781083 entity
Predicate hasGroup P10571 FINISHED
Object Group G
Group G was one of the round-robin groups in the 2016–17 UEFA Europa League, featuring four European football clubs competing for advancement to the knockout stage.
E1925962 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: Group G | Statement: [2016–17 UEFA Europa League, hasGroup, Group G]
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: Group G
Triple: [2016–17 UEFA Europa League, hasGroup, Group G]
Generated description
Group G was one of the round-robin groups in the 2016–17 UEFA Europa League, featuring four European football clubs competing for advancement to the knockout stage.

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_69f224a92f54819095499b4d32bd5134 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68b81f12c8190a0aaacc0a54f9db5 completed May 2, 2026, 11:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28710867a4819087aab7c8e4ae6152 completed June 9, 2026, 8:01 p.m.
NEDg Description generation batch_6a287237c67881908753e11c32ea7efb completed June 9, 2026, 8:06 p.m.
NED2 Entity disambiguation (via description) batch_6a2872cdc6948190ab2904f009993934 completed June 9, 2026, 8:08 p.m.
Created at: April 29, 2026, 8:33 p.m.