Triple

T17451922
Position Surface form Disambiguated ID Type / Status
Subject Wyspa Słodowa E424932 entity
Predicate hasNameInLanguage P15 FINISHED
Object Słodowa Island
Słodowa Island is a small, popular recreational island on the Oder River in Wrocław, Poland, known for its green spaces, cultural events, and views of the historic city center.
E2098444 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: Słodowa Island | Statement: [Wyspa Słodowa, hasNameInLanguage, Słodowa Island]
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: Słodowa Island
Triple: [Wyspa Słodowa, hasNameInLanguage, Słodowa Island]
Generated description
Słodowa Island is a small, popular recreational island on the Oder River in Wrocław, Poland, known for its green spaces, cultural events, and views of the historic city center.

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_69d889db0ba481908402409af3b37917 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4513e57248190824b540865311f44 completed April 19, 2026, 3:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a37210eedac8190af814ff2a1059ac4 completed June 20, 2026, 11:23 p.m.
NEDg Description generation batch_6a37221583e48190a3dbe0dc7ad27453 completed June 20, 2026, 11:28 p.m.
NED2 Entity disambiguation (via description) batch_6a3722b425808190a8453a3e71d14066 completed June 20, 2026, 11:31 p.m.
Created at: April 10, 2026, 5:47 a.m.