Triple

T25139949
Position Surface form Disambiguated ID Type / Status
Subject Hermann II, Count of Celje E629773 entity
Predicate predecessor P97 FINISHED
Object William, Count of Celje
William, Count of Celje was a 14th-century nobleman of the influential House of Celje in what is now Slovenia, known for his role in consolidating the family’s regional power and alliances.
E1673288 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: William, Count of Celje | Statement: [Hermann II, Count of Celje, predecessor, William, Count of Celje]
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: William, Count of Celje
Triple: [Hermann II, Count of Celje, predecessor, William, Count of Celje]
Generated description
William, Count of Celje was a 14th-century nobleman of the influential House of Celje in what is now Slovenia, known for his role in consolidating the family’s regional power and alliances.

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_69e2ff338250819096ff6c8892804389 completed April 18, 2026, 3:49 a.m.
NER Named-entity recognition batch_69f468475218819089b73a0d2e072110 completed May 1, 2026, 8:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1067c0b2a481908cc9cc5052c89411 completed May 22, 2026, 2:27 p.m.
NEDg Description generation batch_6a106ba1c72c8190b06c9ed99e0d9b22 completed May 22, 2026, 2:43 p.m.
NED2 Entity disambiguation (via description) batch_6a106c639f748190bcc45bf86e6b2dfe completed May 22, 2026, 2:46 p.m.
Created at: April 18, 2026, 6:29 a.m.