Triple

T35055151
Position Surface form Disambiguated ID Type / Status
Subject Ivano-Frankivsk Raion E1011440 entity
Predicate previouslyIncludedTerritoriesOf P131869 FINISHED
Object Halych Raion
Halych Raion was a former administrative district in western Ukraine centered around the historic town of Halych in Ivano-Frankivsk Oblast.
E2167846 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: Halych Raion | Statement: [Ivano-Frankivsk Raion, previouslyIncludedTerritoriesOf, Halych 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: Halych Raion
Triple: [Ivano-Frankivsk Raion, previouslyIncludedTerritoriesOf, Halych Raion]
Generated description
Halych Raion was a former administrative district in western Ukraine centered around the historic town of Halych in Ivano-Frankivsk Oblast.

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_69f76dd09c308190a523454853ce842b completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69ff58781b188190a2c7d1656a95d4d7 completed May 9, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38d51d0aa0819093ecce427047fc66 completed June 22, 2026, 6:24 a.m.
NEDg Description generation batch_6a38d58d00c48190b675fee8bef79411 completed June 22, 2026, 6:26 a.m.
NED2 Entity disambiguation (via description) batch_6a38d67cd2c081908e943d16fade52ed completed June 22, 2026, 6:30 a.m.
Created at: May 3, 2026, 4:01 p.m.