Triple

T37896753
Position Surface form Disambiguated ID Type / Status
Subject Hermann IV of Ravensberg E945301 entity
Predicate child P120 FINISHED
Object Margaret of Ravensberg
Margaret of Ravensberg was a 14th-century German noblewoman and heiress whose marriage helped transfer the County of Ravensberg into the possession of the House of Jülich-Berg.
E2284102 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: Margaret of Ravensberg | Statement: [Hermann IV of Ravensberg, child, Margaret of Ravensberg]
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: Margaret of Ravensberg
Triple: [Hermann IV of Ravensberg, child, Margaret of Ravensberg]
Generated description
Margaret of Ravensberg was a 14th-century German noblewoman and heiress whose marriage helped transfer the County of Ravensberg into the possession of the House of Jülich-Berg.

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_69f76ef0e8708190987c7254ed8c7abe completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbbd3bb1f88190a648fadd2175dbf5 completed May 6, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a431e2250c88190a51281a554f573aa completed June 30, 2026, 1:38 a.m.
NEDg Description generation batch_6a431e8bffa08190b42e71f69f443c0a completed June 30, 2026, 1:40 a.m.
NED2 Entity disambiguation (via description) batch_6a431ee60fbc8190a9d931762a58fbda completed June 30, 2026, 1:41 a.m.
Created at: May 3, 2026, 4:19 p.m.