Triple

T36017423
Position Surface form Disambiguated ID Type / Status
Subject Lurë-Dejë National Park E1041882 entity
Predicate locatedIn P40 FINISHED
Object County of Dibër
The County of Dibër is an administrative region in northeastern Albania known for its mountainous landscapes, traditional villages, and protected natural areas.
E2176394 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: County of Dibër | Statement: [Lurë-Dejë National Park, locatedIn, County of Dibër]
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: County of Dibër
Triple: [Lurë-Dejë National Park, locatedIn, County of Dibër]
Generated description
The County of Dibër is an administrative region in northeastern Albania known for its mountainous landscapes, traditional villages, and protected natural areas.

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_69f76e2b981881908e4e160607fa82eb completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7ace0a35c819087293a87666b9f07 completed May 3, 2026, 8:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a396df05ad88190bb73085a73c28144 completed June 22, 2026, 5:16 p.m.
NEDg Description generation batch_6a396ebb4224819081b9d1f60d22b488 completed June 22, 2026, 5:19 p.m.
NED2 Entity disambiguation (via description) batch_6a3970fbbc608190bf438b9446a9be3d completed June 22, 2026, 5:29 p.m.
Created at: May 3, 2026, 4:07 p.m.