Triple

T36860781
Position Surface form Disambiguated ID Type / Status
Subject Prince Heinrich Ruzzo Reuss of Plauen E910929 entity
Predicate givenName P17 FINISHED
Object Heinrich Ruzzo
Heinrich Ruzzo was a German prince of the House of Reuss, known for his aristocratic lineage and marriage to Swedish singer Anni-Frid Lyngstad of ABBA.
E2268821 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 Ruzzo | Statement: [Prince Heinrich Ruzzo Reuss of Plauen, givenName, Heinrich Ruzzo]
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 Ruzzo
Triple: [Prince Heinrich Ruzzo Reuss of Plauen, givenName, Heinrich Ruzzo]
Generated description
Heinrich Ruzzo was a German prince of the House of Reuss, known for his aristocratic lineage and marriage to Swedish singer Anni-Frid Lyngstad of ABBA.

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_69f76e80f6f0819091cba8e19b269615 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7cfcfe7a881908820d8db6e519442 completed May 3, 2026, 10:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41b27fd49c8190a54877cb432b0c7a completed June 28, 2026, 11:47 p.m.
NEDg Description generation batch_6a41b65c93c48190a3847ef7dc430856 completed June 29, 2026, 12:03 a.m.
NED2 Entity disambiguation (via description) batch_6a41b6ad544081909deb23fbd3b629c5 completed June 29, 2026, 12:05 a.m.
Created at: May 3, 2026, 4:13 p.m.