Triple

T34004844
Position Surface form Disambiguated ID Type / Status
Subject Count of Nassau-Dillenburg E871929 entity
Predicate hasTitleHolder P1911 FINISHED
Object John III, Count of Nassau-Dillenburg
John III, Count of Nassau-Dillenburg, was a 16th-century German nobleman of the House of Nassau who ruled the small County of Nassau-Dillenburg within the Holy Roman Empire.
E2092272 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: John III, Count of Nassau-Dillenburg | Statement: [Count of Nassau-Dillenburg, hasTitleHolder, John III, Count of Nassau-Dillenburg]
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: John III, Count of Nassau-Dillenburg
Triple: [Count of Nassau-Dillenburg, hasTitleHolder, John III, Count of Nassau-Dillenburg]
Generated description
John III, Count of Nassau-Dillenburg, was a 16th-century German nobleman of the House of Nassau who ruled the small County of Nassau-Dillenburg within the Holy Roman Empire.

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_69f349a08848819084b348d64c1879c3 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f70ac5a9508190a03efb6ff8b9a7d1 completed May 3, 2026, 8:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36f9abe3b48190836c1863707c49b3 completed June 20, 2026, 8:35 p.m.
NEDg Description generation batch_6a36fa7cf07c819080d18e1c419568f7 completed June 20, 2026, 8:39 p.m.
NED2 Entity disambiguation (via description) batch_6a36fe233bb8819096419ecbfeebc79b completed June 20, 2026, 8:54 p.m.
Created at: May 1, 2026, 1:50 a.m.