Triple

T31507657
Position Surface form Disambiguated ID Type / Status
Subject 7TP E803859 entity
Predicate armamentPrimary P6066 FINISHED
Object 37 mm Bofors wz. 37 gun
The 37 mm Bofors wz. 37 gun was a Polish-made, Swedish-designed anti-tank and tank gun widely used as the main armament on pre–World War II Polish light tanks and tankettes.
 E1965598 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: 37 mm Bofors wz. 37 gun | Statement: [7TP, armamentPrimary, 37 mm Bofors wz. 37 gun]
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: 37 mm Bofors wz. 37 gun
Triple: [7TP, armamentPrimary, 37 mm Bofors wz. 37 gun]
Generated description
The 37 mm Bofors wz. 37 gun was a Polish-made, Swedish-designed anti-tank and tank gun widely used as the main armament on pre–World War II Polish light tanks and tankettes.

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_69f348ceb0a48190ae7feca263b6296c completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a21826308190b12c2e8d6ab218d5 completed May 3, 2026, 1:17 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b147306248190b8be73d3b90527d1 completed June 11, 2026, 8:02 p.m.
NEDg Description generation batch_6a2b1631ffcc8190bf1c512953e526f6 completed June 11, 2026, 8:10 p.m.
NED2 Entity disambiguation (via description) batch_6a2b18c22a48819084a8414aee86ca35 completed June 11, 2026, 8:21 p.m.
Created at: April 30, 2026, 9:48 p.m.