Triple

T25912686
Position Surface form Disambiguated ID Type / Status
Subject Gmina Łącko E652938 entity
Predicate seat P75 FINISHED
Object Łącko
Łącko is a village in southern Poland known for its picturesque location in the Beskid Sądecki region and its traditional fruit orchards and plum brandy.
E2264192 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: Łącko | Statement: [Gmina Łącko, seat, Łącko]
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: Łącko
Triple: [Gmina Łącko, seat, Łącko]
Generated description
Łącko is a village in southern Poland known for its picturesque location in the Beskid Sądecki region and its traditional fruit orchards and plum brandy.

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_69e7ab3e025c819086771607157f0015 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f603c67f0c8190be8443cfa6e991b2 completed May 2, 2026, 2:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a419ddaef408190a14d8eed3a94fc65 completed June 28, 2026, 10:19 p.m.
NEDg Description generation batch_6a419f2252288190a5c82877f6e06af7 completed June 28, 2026, 10:24 p.m.
NED2 Entity disambiguation (via description) batch_6a419fc808308190a4b9f96e219b9d82 completed June 28, 2026, 10:27 p.m.
Created at: April 22, 2026, 8:30 a.m.