Triple

T28869588
Position Surface form Disambiguated ID Type / Status
Subject Princess Augusta Wilhelmine of Hesse-Darmstadt E729104 entity
Predicate child P120 FINISHED
Object Charlotte of Bavaria
Charlotte of Bavaria was a Bavarian princess of the late 18th and early 19th centuries who became known as a member of the Wittelsbach dynasty through her marriage into the Bavarian royal family.
E2294589 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: Charlotte of Bavaria | Statement: [Princess Augusta Wilhelmine of Hesse-Darmstadt, child, Charlotte of Bavaria]
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: Charlotte of Bavaria
Triple: [Princess Augusta Wilhelmine of Hesse-Darmstadt, child, Charlotte of Bavaria]
Generated description
Charlotte of Bavaria was a Bavarian princess of the late 18th and early 19th centuries who became known as a member of the Wittelsbach dynasty through her marriage into the Bavarian royal family.

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_69f031a01cbc8190ba87270bb6fe4639 completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f65a45253481909791cec9f0b64072 completed May 2, 2026, 8:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7c023a30148190984b3e9ae28b3aa7 completed Aug. 12, 2026, 5:18 a.m.
NEDg Description generation batch_6a7c02cc79dc8190a2301577ccb2c0ca completed Aug. 12, 2026, 5:21 a.m.
NED2 Entity disambiguation (via description) batch_6a7c031a3c4c8190bd1d0e84b5c5da71 completed Aug. 12, 2026, 5:22 a.m.
Created at: April 28, 2026, 6:50 a.m.