Triple

T28239129
Position Surface form Disambiguated ID Type / Status
Subject Archibald Primrose, 4th Earl of Rosebery E711970 entity
Predicate child P120 FINISHED
Object Neil Primrose
Neil Primrose was a British Liberal politician and soldier who served as a Member of Parliament and was killed in action during World War I.
E1809593 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: Neil Primrose | Statement: [Archibald Primrose, 4th Earl of Rosebery, child, Neil Primrose]
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: Neil Primrose
Triple: [Archibald Primrose, 4th Earl of Rosebery, child, Neil Primrose]
Generated description
Neil Primrose was a British Liberal politician and soldier who served as a Member of Parliament and was killed in action during World War I.

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_69efb51ece308190b8c269a057e36652 completed April 27, 2026, 7:12 p.m.
NER Named-entity recognition batch_69f643c3aab88190842770d1bc058c07 completed May 2, 2026, 6:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15e6d1c2a48190ba0c43bfd0cfcbdb completed May 26, 2026, 6:30 p.m.
NEDg Description generation batch_6a15e7d2fef48190afc3d5ee7901ebac completed May 26, 2026, 6:34 p.m.
NED2 Entity disambiguation (via description) batch_6a15fcfcbb94819096d38b205a60ba4a completed May 26, 2026, 8:05 p.m.
Created at: April 27, 2026, 10:57 p.m.