Triple

T31189694
Position Surface form Disambiguated ID Type / Status
Subject Jász-Nagykun-Szolnok County E795146 entity
Predicate hasPart P35 FINISHED
Object Nagykunság
Nagykunság is a historical and ethnographic region in central Hungary traditionally inhabited by the Cumans and known for its distinctive cultural heritage and Great Hungarian Plain landscapes.
E1950671 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: Nagykunság | Statement: [Jász-Nagykun-Szolnok County, hasPart, Nagykunság]
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: Nagykunság
Triple: [Jász-Nagykun-Szolnok County, hasPart, Nagykunság]
Generated description
Nagykunság is a historical and ethnographic region in central Hungary traditionally inhabited by the Cumans and known for its distinctive cultural heritage and Great Hungarian Plain 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_69f224d7a6a481908187c4362a8a525f completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69913d91c81908d00dc873428367b completed May 3, 2026, 12:38 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2959141f6481908bd2c49769476564 completed June 10, 2026, 12:31 p.m.
NEDg Description generation batch_6a295a7d152881908a6b3341e121928c completed June 10, 2026, 12:37 p.m.
NED2 Entity disambiguation (via description) batch_6a295b05450c8190ab6eea66561a3a26 completed June 10, 2026, 12:39 p.m.
Created at: April 29, 2026, 9:08 p.m.