Triple

T37482436
Position Surface form Disambiguated ID Type / Status
Subject Battenberg–Mountbatten line E931444 entity
Predicate notableMember P10 FINISHED
Object Prince George of Battenberg
Prince George of Battenberg was a minor German-British prince from the Battenberg–Mountbatten family, connected to European royal and noble circles.
E2231573 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 George of Battenberg | Statement: [Battenberg–Mountbatten line, notableMember, Prince George of Battenberg]
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 George of Battenberg
Triple: [Battenberg–Mountbatten line, notableMember, Prince George of Battenberg]
Generated description
Prince George of Battenberg was a minor German-British prince from the Battenberg–Mountbatten family, connected to European royal and noble circles.

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_69f76ec382248190b47844df596123c6 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fba35692b88190b422d37edde723fe completed May 6, 2026, 8:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a409ef778b08190878d597281b090ca completed June 28, 2026, 4:11 a.m.
NEDg Description generation batch_6a409f79e0408190b706813e9af454eb completed June 28, 2026, 4:13 a.m.
NED2 Entity disambiguation (via description) batch_6a409fdd788c819086a875fe7c2d1aa3 completed June 28, 2026, 4:15 a.m.
Created at: May 3, 2026, 4:17 p.m.