Triple

T25677519
Position Surface form Disambiguated ID Type / Status
Subject Siege of Namur E643846 entity
Predicate defensiveForce P375 FINISHED
Object Belgian 4th Division
The Belgian 4th Division was a World War I Belgian Army infantry formation that notably took part in the early fighting during the German invasion of Belgium, including the defense of key fortified positions.
E1689985 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: Belgian 4th Division | Statement: [Siege of Namur, defensiveForce, Belgian 4th Division]
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: Belgian 4th Division
Triple: [Siege of Namur, defensiveForce, Belgian 4th Division]
Generated description
The Belgian 4th Division was a World War I Belgian Army infantry formation that notably took part in the early fighting during the German invasion of Belgium, including the defense of key fortified positions.

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_69e77e7f69808190ad27df1006f6037a completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f5fb7700888190a773a390033bf320 completed May 2, 2026, 1:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10c15d396881909a0825c45463dc38 completed May 22, 2026, 8:49 p.m.
NEDg Description generation batch_6a10c1f3ae208190b3cdc518e83bbc7f completed May 22, 2026, 8:52 p.m.
NED2 Entity disambiguation (via description) batch_6a10c2b5aab88190ab29798dc74baacf completed May 22, 2026, 8:55 p.m.
Created at: April 21, 2026, 7:41 p.m.