Triple

T17425645
Position Surface form Disambiguated ID Type / Status
Subject Battle of Cherbourg E423730 entity
Predicate commander P1061 FINISHED
Object Walter Hennecke
Walter Hennecke was a German naval officer and rear admiral in the Kriegsmarine during World War II, noted for his leadership in coastal defense operations against the Allied invasion of France.
E1828574 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: Walter Hennecke | Statement: [Battle of Cherbourg, commander, Walter Hennecke]
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: Walter Hennecke
Triple: [Battle of Cherbourg, commander, Walter Hennecke]
Generated description
Walter Hennecke was a German naval officer and rear admiral in the Kriegsmarine during World War II, noted for his leadership in coastal defense operations against the Allied invasion of France.

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_69d889d88b6081908bada047f5b3ba51 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e448fbfda88190be1c001d64289bf7 completed April 19, 2026, 3:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1cc34b59508190b1587ae59de04eef completed May 31, 2026, 11:24 p.m.
NEDg Description generation batch_6a1cc44ac1448190b0dc305eb5e460be completed May 31, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a1cc571b3b481908c523e5bad5e086a completed May 31, 2026, 11:34 p.m.
Created at: April 10, 2026, 5:46 a.m.