Triple

T31990012
Position Surface form Disambiguated ID Type / Status
Subject 152 mm ShKH vz. 77 DANA E816837 entity
Predicate successor P78 FINISHED
Object 155 mm ShKH Zuzana
The 155 mm ShKH Zuzana is a Slovak self-propelled howitzer featuring a 155 mm NATO-standard gun, advanced fire-control systems, and improved mobility and protection over its predecessor.
 E1986068 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: 155 mm ShKH Zuzana | Statement: [152 mm ShKH vz. 77 DANA, successor, 155 mm ShKH Zuzana]
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: 155 mm ShKH Zuzana
Triple: [152 mm ShKH vz. 77 DANA, successor, 155 mm ShKH Zuzana]
Generated description
The 155 mm ShKH Zuzana is a Slovak self-propelled howitzer featuring a 155 mm NATO-standard gun, advanced fire-control systems, and improved mobility and protection over its predecessor.

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_69f348f8002081909a3588758ba94afb completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b3b8e360819095a9882acb3e3d21 completed May 3, 2026, 2:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2eb15784348190a40b784ea4de7f0d completed June 14, 2026, 1:49 p.m.
NEDg Description generation batch_6a2eb1cef8488190a83ff06da4bf30c5 completed June 14, 2026, 1:51 p.m.
NED2 Entity disambiguation (via description) batch_6a2eb25edcbc8190902aeaed0a8f9590 completed June 14, 2026, 1:53 p.m.
Created at: May 1, 2026, 12:13 a.m.