Triple

T35727430
Position Surface form Disambiguated ID Type / Status
Subject Henry X of Haynau E1032653 entity
Predicate title P38 FINISHED
Object Duke of Haynau
The Duke of Haynau was a medieval Silesian noble title held by members of the Piast dynasty who ruled the duchy centered on the town of Haynau (now Chojnów in Poland).
E2250360 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: Duke of Haynau | Statement: [Henry X of Haynau, title, Duke of Haynau]
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: Duke of Haynau
Triple: [Henry X of Haynau, title, Duke of Haynau]
Generated description
The Duke of Haynau was a medieval Silesian noble title held by members of the Piast dynasty who ruled the duchy centered on the town of Haynau (now Chojnów in Poland).

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_69f76e102b5881909e5d63a30a5cecbe completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a131fc3881909d9897e52ca4f546 completed May 3, 2026, 7:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4117cdb70c8190b8e83f42e26845e0 completed June 28, 2026, 12:47 p.m.
NEDg Description generation batch_6a4118db6bfc8190827969ae9f6ca62b completed June 28, 2026, 12:51 p.m.
NED2 Entity disambiguation (via description) batch_6a412489986c8190b86728ae7f1d1c06 completed June 28, 2026, 1:41 p.m.
Created at: May 3, 2026, 4:05 p.m.