Triple

T28185247
Position Surface form Disambiguated ID Type / Status
Subject House of Arco-Zinneberg E716159 entity
Predicate styleOfAddress P536 FINISHED
Object Countess of Arco-Zinneberg
The Countess of Arco-Zinneberg is a noble title held by female members of the historic Bavarian aristocratic House of Arco-Zinneberg.
E1822641 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: Countess of Arco-Zinneberg | Statement: [House of Arco-Zinneberg, styleOfAddress, Countess of Arco-Zinneberg]
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: Countess of Arco-Zinneberg
Triple: [House of Arco-Zinneberg, styleOfAddress, Countess of Arco-Zinneberg]
Generated description
The Countess of Arco-Zinneberg is a noble title held by female members of the historic Bavarian aristocratic House of Arco-Zinneberg.

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_69efd6b4fc5c81909dd88f01a8c2b35d completed April 27, 2026, 9:35 p.m.
NER Named-entity recognition batch_69f64285d75481908da4a276fd8c4676 completed May 2, 2026, 6:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cac27a48c819082020f586c5704c8 completed May 31, 2026, 9:46 p.m.
NEDg Description generation batch_6a1cacfc26bc8190ad65e3f8ef7d6d7b completed May 31, 2026, 9:49 p.m.
NED2 Entity disambiguation (via description) batch_6a1cadfb2d808190b2b46e8e2b7e2274 completed May 31, 2026, 9:54 p.m.
Created at: April 27, 2026, 10:22 p.m.