Triple

T24816407
Position Surface form Disambiguated ID Type / Status
Subject Utena County E620933 entity
Predicate containsAdministrativeUnit P3892 FINISHED
Object Utena District Municipality
Utena District Municipality is a local government area in northeastern Lithuania, centered on the town of Utena and known for its lakes and natural landscapes.
E1744807 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: Utena District Municipality | Statement: [Utena County, containsAdministrativeUnit, Utena District Municipality]
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: Utena District Municipality
Triple: [Utena County, containsAdministrativeUnit, Utena District Municipality]
Generated description
Utena District Municipality is a local government area in northeastern Lithuania, centered on the town of Utena and known for its lakes and natural landscapes.

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_69e2fabfd4648190bd0e5c7f4dbb6cab completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f4229401148190ab5b57da94aea80d completed May 1, 2026, 3:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1212fce3608190a3528195d02f18fa completed May 23, 2026, 8:50 p.m.
NEDg Description generation batch_6a12150278448190b2538abe4f8d2e6f completed May 23, 2026, 8:58 p.m.
NED2 Entity disambiguation (via description) batch_6a1215ea04d481909f626eb762160a85 completed May 23, 2026, 9:02 p.m.
Created at: April 18, 2026, 5:02 a.m.