Triple

T21278142
Position Surface form Disambiguated ID Type / Status
Subject Prince-Bishopric of Fulda E524444 entity
Predicate notableRuler P22 FINISHED
Object Heinrich von Bibra
Heinrich von Bibra was an 18th-century German prince-bishop and statesman known for his enlightened reforms and governance of the Prince-Bishopric of Fulda.
E1777386 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 von Bibra | Statement: [Prince-Bishopric of Fulda, notableRuler, Heinrich von Bibra]
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 von Bibra
Triple: [Prince-Bishopric of Fulda, notableRuler, Heinrich von Bibra]
Generated description
Heinrich von Bibra was an 18th-century German prince-bishop and statesman known for his enlightened reforms and governance of the Prince-Bishopric of Fulda.

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_69e0b516293c819089458ea2ec85f85e completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e73658f598819098a1192abfa40a12 completed April 21, 2026, 8:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a12c5788db48190820d5d3e09bc2d51 completed May 24, 2026, 9:31 a.m.
NEDg Description generation batch_6a12c7206c4c819099dcb58763f4d491 completed May 24, 2026, 9:38 a.m.
NED2 Entity disambiguation (via description) batch_6a12c79229e08190830d0c8f139a228c completed May 24, 2026, 9:40 a.m.
Created at: April 16, 2026, 4:02 p.m.