Triple

T30784345
Position Surface form Disambiguated ID Type / Status
Subject Gmina Świętajno (Olecko County) E783913 entity
Predicate hasSettlement P1068 FINISHED
Object Dunajek
Dunajek is a small village located in the administrative district of Gmina Świętajno in Olecko County, northeastern Poland.
E1950888 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: Dunajek | Statement: [Gmina Świętajno (Olecko County), hasSettlement, Dunajek]
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: Dunajek
Triple: [Gmina Świętajno (Olecko County), hasSettlement, Dunajek]
Generated description
Dunajek is a small village located in the administrative district of Gmina Świętajno in Olecko County, northeastern Poland.

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_69f224b213c8819083886073f90b647e completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f68fe6f744819083f8ee5a6b846929 completed May 2, 2026, 11:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2958f12d2c8190bf39a3f11b5742b3 completed June 10, 2026, 12:30 p.m.
NEDg Description generation batch_6a295b959da48190ab55284ed78d9674 completed June 10, 2026, 12:41 p.m.
NED2 Entity disambiguation (via description) batch_6a295c0c15648190abc3dc9308e2ed61 completed June 10, 2026, 12:43 p.m.
Created at: April 29, 2026, 8:41 p.m.