Triple

T38298369
Position Surface form Disambiguated ID Type / Status
Subject Przemysł I of Greater Poland E1032155 entity
Predicate positionHeld P8 FINISHED
Object Duke of Lubusz
The Duke of Lubusz was a medieval Polish noble title associated with ruling the strategically important Lubusz (Lebus) region on the Oder River.
E2285022 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 Lubusz | Statement: [Przemysł I of Greater Poland, positionHeld, Duke of Lubusz]
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 Lubusz
Triple: [Przemysł I of Greater Poland, positionHeld, Duke of Lubusz]
Generated description
The Duke of Lubusz was a medieval Polish noble title associated with ruling the strategically important Lubusz (Lebus) region on the Oder River.

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_6a44b3916758819092544ab28c7b5afa completed July 1, 2026, 6:28 a.m.
NEDg Description generation batch_6a44b587c3ec8190997b70be1d8c7c15 completed July 1, 2026, 6:36 a.m.
NED2 Entity disambiguation (via description) batch_6a44b5e52690819086e95e560158612c completed July 1, 2026, 6:38 a.m.
Created at: May 3, 2026, 4:30 p.m.