Triple

T33890288
Position Surface form Disambiguated ID Type / Status
Subject Bourbon-Orléans branch E868740 entity
Predicate notableSeat P19696 FINISHED
Object Château de Randan
The Château de Randan is a historic French royal residence in the Auvergne region, closely associated with the 19th-century Orléans branch of the Bourbon dynasty.
E2072082 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: Château de Randan | Statement: [Bourbon-Orléans branch, notableSeat, Château de Randan]
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: Château de Randan
Triple: [Bourbon-Orléans branch, notableSeat, Château de Randan]
Generated description
The Château de Randan is a historic French royal residence in the Auvergne region, closely associated with the 19th-century Orléans branch of the Bourbon dynasty.

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_69f34996761c8190864e42f7c9cf215b completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f701444ce48190b4c30a6174dc10c7 completed May 3, 2026, 8:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36763625f481908fb822b5e49937ee completed June 20, 2026, 11:15 a.m.
NEDg Description generation batch_6a36784d524481909e1bb8a7cdb3fdd2 completed June 20, 2026, 11:23 a.m.
NED2 Entity disambiguation (via description) batch_6a3678a05f2c8190a9976e7ab475187f completed June 20, 2026, 11:25 a.m.
Created at: May 1, 2026, 1:48 a.m.