Triple

T33955299
Position Surface form Disambiguated ID Type / Status
Subject starost of Kałusz E870552 entity
Predicate appliesToJurisdiction P82 FINISHED
Object Kałusz district
Kałusz district was an administrative district in the historical region of Galicia, centered on the town of Kałusz (now Kalush in western Ukraine), that functioned under the authority of a starost.
E2076479 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: Kałusz district | Statement: [starost of Kałusz, appliesToJurisdiction, Kałusz district]
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: Kałusz district
Triple: [starost of Kałusz, appliesToJurisdiction, Kałusz district]
Generated description
Kałusz district was an administrative district in the historical region of Galicia, centered on the town of Kałusz (now Kalush in western Ukraine), that functioned under the authority of a starost.

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_69f3499c2d7481909c953a5010227725 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f7027cc5488190a122f7bd1b4f3f7e completed May 3, 2026, 8:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3692d2e5f88190be65654fec37f5e4 completed June 20, 2026, 1:17 p.m.
NEDg Description generation batch_6a3693820ad081909280cf562695e90f completed June 20, 2026, 1:20 p.m.
NED2 Entity disambiguation (via description) batch_6a36941c84ac8190ab0f8f338320ceec completed June 20, 2026, 1:22 p.m.
Created at: May 1, 2026, 1:49 a.m.