Triple

T35669632
Position Surface form Disambiguated ID Type / Status
Subject Pristina District E1030674 entity
Predicate containsAdministrativeTerritorialEntity P747 FINISHED
Object Municipality of Drenas
The Municipality of Drenas is a local government area in central Kosovo known for its industrial activities and proximity to the capital, Pristina.
E2155685 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: Municipality of Drenas | Statement: [Pristina District, containsAdministrativeTerritorialEntity, Municipality of Drenas]
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: Municipality of Drenas
Triple: [Pristina District, containsAdministrativeTerritorialEntity, Municipality of Drenas]
Generated description
The Municipality of Drenas is a local government area in central Kosovo known for its industrial activities and proximity to the capital, Pristina.

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_69f76e0acfc0819082c8495c2210ce73 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79fb10c4881908b12bfceaaf085f1 completed May 3, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38914f56c88190828a8f3bbd78a053 completed June 22, 2026, 1:35 a.m.
NEDg Description generation batch_6a3891dc79dc8190bf2482158e0dabed completed June 22, 2026, 1:37 a.m.
NED2 Entity disambiguation (via description) batch_6a38925d7c688190afca1a703aea06c3 completed June 22, 2026, 1:39 a.m.
Created at: May 3, 2026, 4:05 p.m.