Triple

T31687721
Position Surface form Disambiguated ID Type / Status
Subject Erbach family E808705 entity
Predicate notableMember P10 FINISHED
Object Alexander, Count of Erbach-Schönberg
Alexander, Count of Erbach-Schönberg was a German nobleman from the House of Erbach who served as a courtier and held various positions within the aristocratic society of the Grand Duchy of Hesse.
E2010440 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: Alexander, Count of Erbach-Schönberg | Statement: [Erbach family, notableMember, Alexander, Count of Erbach-Schönberg]
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: Alexander, Count of Erbach-Schönberg
Triple: [Erbach family, notableMember, Alexander, Count of Erbach-Schönberg]
Generated description
Alexander, Count of Erbach-Schönberg was a German nobleman from the House of Erbach who served as a courtier and held various positions within the aristocratic society of the Grand Duchy of Hesse.

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_69f348ddcbc48190950cabcc25ff29b3 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6aa7e50108190a70942725d12bb64 completed May 3, 2026, 1:53 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34702d68dc819088602b04eae4351b completed June 18, 2026, 10:24 p.m.
NEDg Description generation batch_6a34710734988190a0a6880097a6a639 completed June 18, 2026, 10:28 p.m.
NED2 Entity disambiguation (via description) batch_6a3471ce69508190bbd47938ea429317 completed June 18, 2026, 10:31 p.m.
Created at: April 30, 2026, 11:07 p.m.