Triple

T34952127
Position Surface form Disambiguated ID Type / Status
Subject Henry of Carinthia E1008027 entity
Predicate sibling P363 FINISHED
Object Otto III of Carinthia
Otto III of Carinthia was a late 13th- to early 14th-century nobleman who ruled as Duke of Carinthia and Count of Tyrol within the Holy Roman Empire.
E2137979 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: Otto III of Carinthia | Statement: [Henry of Carinthia, sibling, Otto III of Carinthia]
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: Otto III of Carinthia
Triple: [Henry of Carinthia, sibling, Otto III of Carinthia]
Generated description
Otto III of Carinthia was a late 13th- to early 14th-century nobleman who ruled as Duke of Carinthia and Count of Tyrol 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_69f76dc5d4308190b77553ee07b1ede6 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f782cea4c881908ada116c80eafa15 completed May 3, 2026, 5:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a382c9b2358819082e88577f0c96fbc completed June 21, 2026, 6:25 p.m.
NEDg Description generation batch_6a382d21cd8881909249e6762bde2ae2 completed June 21, 2026, 6:27 p.m.
NED2 Entity disambiguation (via description) batch_6a382d8e54608190a7de6942dfe3801a completed June 21, 2026, 6:29 p.m.
Created at: May 3, 2026, 4 p.m.