Triple

T27486871
Position Surface form Disambiguated ID Type / Status
Subject Reuss of Ebersdorf E693761 entity
Predicate hasMember P10 FINISHED
Object Heinrich XLVI, Count Reuss of Ebersdorf
Heinrich XLVI, Count Reuss of Ebersdorf was a German nobleman of the House of Reuss who ruled the small Thuringian county of Ebersdorf in the 18th century.
E1870310 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: Heinrich XLVI, Count Reuss of Ebersdorf | Statement: [Reuss of Ebersdorf, hasMember, Heinrich XLVI, Count Reuss of Ebersdorf]
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: Heinrich XLVI, Count Reuss of Ebersdorf
Triple: [Reuss of Ebersdorf, hasMember, Heinrich XLVI, Count Reuss of Ebersdorf]
Generated description
Heinrich XLVI, Count Reuss of Ebersdorf was a German nobleman of the House of Reuss who ruled the small Thuringian county of Ebersdorf in the 18th century.

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_69ef5382b9648190be0b1ef2ad5d043c completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62e8544ec8190864108497a8d8ad0 completed May 2, 2026, 5:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25f0e307e88190a11761a5f81a627d completed June 7, 2026, 10:29 p.m.
NEDg Description generation batch_6a25f67f6bc88190af7c53158288e611 completed June 7, 2026, 10:53 p.m.
NED2 Entity disambiguation (via description) batch_6a25fab29d588190a93a4b1043036423 completed June 7, 2026, 11:11 p.m.
Created at: April 27, 2026, 1:03 p.m.