Triple

T33963257
Position Surface form Disambiguated ID Type / Status
Subject Dunaivtsi E870777 entity
Predicate partOf P40 FINISHED
Object Dunaivtsi Raion
Dunaivtsi Raion was an administrative district in Khmelnytskyi Oblast, western Ukraine, centered around the town of Dunaivtsi until its abolition in the 2020 administrative reform.
E2149107 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: Dunaivtsi Raion | Statement: [Dunaivtsi, partOf, Dunaivtsi Raion]
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: Dunaivtsi Raion
Triple: [Dunaivtsi, partOf, Dunaivtsi Raion]
Generated description
Dunaivtsi Raion was an administrative district in Khmelnytskyi Oblast, western Ukraine, centered around the town of Dunaivtsi until its abolition in the 2020 administrative reform.

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_69f3499ce8e88190b66e1d49ad8c7037 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f702ccf1608190a30d2462b65b53de completed May 3, 2026, 8:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a386829c2fc81909673393043f88bce completed June 21, 2026, 10:39 p.m.
NEDg Description generation batch_6a386913196c81908274a2e909d943b8 completed June 21, 2026, 10:43 p.m.
NED2 Entity disambiguation (via description) batch_6a3869ecb09c8190bffe477099dcc2cf completed June 21, 2026, 10:47 p.m.
Created at: May 1, 2026, 1:50 a.m.