Triple

T37052254
Position Surface form Disambiguated ID Type / Status
Subject IBM tape libraries E917078 entity
Predicate supportsDriveTechnology P205704 FINISHED
Object IBM 3592 tape drives
IBM 3592 tape drives are high-capacity, enterprise-class magnetic tape storage devices designed for data backup, archiving, and long-term retention in large-scale IT environments.
E2210204 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: IBM 3592 tape drives | Statement: [IBM tape libraries, supportsDriveTechnology, IBM 3592 tape drives]
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: IBM 3592 tape drives
Triple: [IBM tape libraries, supportsDriveTechnology, IBM 3592 tape drives]
Generated description
IBM 3592 tape drives are high-capacity, enterprise-class magnetic tape storage devices designed for data backup, archiving, and long-term retention in large-scale IT environments.

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_69f76e94d0308190a3f06890e133c88e completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_6a03809cd8cc8190a0b502998be65a15 completed May 12, 2026, 7:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e8c4d51a08190ad308c80bffd8f71 completed June 26, 2026, 2:27 p.m.
NEDg Description generation batch_6a3e97fc8f74819086ff55cfa8425daf completed June 26, 2026, 3:17 p.m.
NED2 Entity disambiguation (via description) batch_6a3e987d99e48190a261ef966073f3f6 completed June 26, 2026, 3:19 p.m.
Created at: May 3, 2026, 4:14 p.m.