Triple

T32730013
Position Surface form Disambiguated ID Type / Status
Subject K1A1 E836922 entity
Predicate hasUpgradeOver P5357 FINISHED
Object K1 105 mm gun
The K1 105 mm gun is the original main armament of South Korea’s K1 series main battle tanks, designed to fire NATO-standard 105 mm ammunition.
 E2020018 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: K1 105 mm gun | Statement: [K1A1, hasUpgradeOver, K1 105 mm 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: K1 105 mm gun
Triple: [K1A1, hasUpgradeOver, K1 105 mm gun]
Generated description
The K1 105 mm gun is the original main armament of South Korea’s K1 series main battle tanks, designed to fire NATO-standard 105 mm ammunition.

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_69f34935fb048190ad4967420581f835 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6c8cbb9248190a13b712c81948822 completed May 3, 2026, 4:02 a.m.
NED1 Entity disambiguation (via context triple) batch_6a349edab1f08190a485b9122a42f422 completed June 19, 2026, 1:43 a.m.
NEDg Description generation batch_6a34a0590c70819089184be6ef8edfdc completed June 19, 2026, 1:50 a.m.
NED2 Entity disambiguation (via description) batch_6a34a1248dcc8190b754cabe14a9d9ae completed June 19, 2026, 1:53 a.m.
Created at: May 1, 2026, 1:11 a.m.