Triple

T38298366
Position Surface form Disambiguated ID Type / Status
Subject Przemysł I of Greater Poland E1032155 entity
Predicate positionHeld P8 FINISHED
Object Duke of Czarnków
The Duke of Czarnków was a medieval Polish noble title associated with the Piast dynasty’s rule over the Czarnków region in Greater Poland.
E2284779 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: Duke of Czarnków | Statement: [Przemysł I of Greater Poland, positionHeld, Duke of Czarnków]
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: Duke of Czarnków
Triple: [Przemysł I of Greater Poland, positionHeld, Duke of Czarnków]
Generated description
The Duke of Czarnków was a medieval Polish noble title associated with the Piast dynasty’s rule over the Czarnków region in Greater Poland.

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_69f76e0f2084819091299d021625c3fe completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69fcc618020c8190b055d8c8d4d7c050 completed May 7, 2026, 5:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a44a35b3f2481908c8181455730e223 completed July 1, 2026, 5:19 a.m.
NEDg Description generation batch_6a44a3b3cac881908bf0781b85fc8203 completed July 1, 2026, 5:20 a.m.
NED2 Entity disambiguation (via description) batch_6a44a4d30d908190a61ae6309bb80dad completed July 1, 2026, 5:25 a.m.
Created at: May 3, 2026, 4:30 p.m.