Triple

T37493282
Position Surface form Disambiguated ID Type / Status
Subject John II, Margrave of Brandenburg E931754 entity
Predicate spouse P13 FINISHED
Object Hedwig of Werle
Hedwig of Werle was a medieval German noblewoman from the House of Werle who became Margravine of Brandenburg through her marriage to John II, Margrave of Brandenburg.
E2228915 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: Hedwig of Werle | Statement: [John II, Margrave of Brandenburg, spouse, Hedwig of Werle]
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: Hedwig of Werle
Triple: [John II, Margrave of Brandenburg, spouse, Hedwig of Werle]
Generated description
Hedwig of Werle was a medieval German noblewoman from the House of Werle who became Margravine of Brandenburg through her marriage to John II, Margrave of Brandenburg.

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_69f76ec457a4819094eeb3aed9baac11 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fba37cebe08190a8bd035faca7dc13 completed May 6, 2026, 8:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a408c48a47c819090223d8014e32773 completed June 28, 2026, 2:51 a.m.
NEDg Description generation batch_6a408dcfa3d88190b70579dceeaf8eb7 completed June 28, 2026, 2:58 a.m.
NED2 Entity disambiguation (via description) batch_6a408e95b7dc8190a6b7cf7a355f2966 completed June 28, 2026, 3:01 a.m.
Created at: May 3, 2026, 4:17 p.m.