Triple

T29757888
Position Surface form Disambiguated ID Type / Status
Subject European Green Capital 2021 E753078 entity
Predicate relatedProgramme P6928 FINISHED
Object European Green Leaf Award
The European Green Leaf Award is a European Commission initiative that recognizes and promotes the environmental performance and sustainable development efforts of smaller cities across Europe.
E1883077 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: European Green Leaf Award | Statement: [European Green Capital 2021, relatedProgramme, European Green Leaf Award]
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: European Green Leaf Award
Triple: [European Green Capital 2021, relatedProgramme, European Green Leaf Award]
Generated description
The European Green Leaf Award is a European Commission initiative that recognizes and promotes the environmental performance and sustainable development efforts of smaller cities across Europe.

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_69f0d62c84cc8190846f80ae04fdf8ec completed April 28, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f673cd0a688190903dc64d4e5b5571 completed May 2, 2026, 9:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26c8eaef148190b6747fbab1c460b5 completed June 8, 2026, 1:51 p.m.
NEDg Description generation batch_6a26d3e241d48190a6f6efa891fb5aa3 completed June 8, 2026, 2:38 p.m.
NED2 Entity disambiguation (via description) batch_6a26d48a1ec481908b497e0f7a4d60a3 completed June 8, 2026, 2:41 p.m.
Created at: April 28, 2026, 7:57 p.m.