Triple

T26221393
Position Surface form Disambiguated ID Type / Status
Subject Kaunitz family E655771 entity
Predicate hereditaryTitle P1913 FINISHED
Object Prince of Kaunitz-Rietberg
The Prince of Kaunitz-Rietberg was a noble title held by a prominent Austro-Bohemian aristocratic family influential in Habsburg imperial politics.
E1731824 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: Prince of Kaunitz-Rietberg | Statement: [Kaunitz family, hereditaryTitle, Prince of Kaunitz-Rietberg]
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: Prince of Kaunitz-Rietberg
Triple: [Kaunitz family, hereditaryTitle, Prince of Kaunitz-Rietberg]
Generated description
The Prince of Kaunitz-Rietberg was a noble title held by a prominent Austro-Bohemian aristocratic family influential in Habsburg imperial politics.

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_69ee5b4a77e08190bfcb5f8ecdc55abd completed April 26, 2026, 6:36 p.m.
NER Named-entity recognition batch_69f60d5060708190b3134a5e5a4ca850 completed May 2, 2026, 2:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11c7f1677081909c27f7bd222582ca completed May 23, 2026, 3:29 p.m.
NEDg Description generation batch_6a11c945273c8190ac0bc6fe508a6d9a completed May 23, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_6a11ca6f162c8190a8c7fbc1e188ea90 completed May 23, 2026, 3:40 p.m.
Created at: April 26, 2026, 8:56 p.m.