Triple

T33063531
Position Surface form Disambiguated ID Type / Status
Subject HP inkjet supplies portfolio E846034 entity
Predicate supportsPrinterFamily P57888 FINISHED
Object HP DesignJet printers
HP DesignJet printers are large-format inkjet printers from HP designed for high-quality, wide-format printing applications such as CAD drawings, GIS maps, and professional graphics.
E2034454 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: HP DesignJet printers | Statement: [HP inkjet supplies portfolio, supportsPrinterFamily, HP DesignJet printers]
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: HP DesignJet printers
Triple: [HP inkjet supplies portfolio, supportsPrinterFamily, HP DesignJet printers]
Generated description
HP DesignJet printers are large-format inkjet printers from HP designed for high-quality, wide-format printing applications such as CAD drawings, GIS maps, and professional graphics.

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_69f3495333b8819095e9af56855b9061 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_6a03809967388190bfdc58bda40bd3fc completed May 12, 2026, 7:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a34e525cc3881909e6c57f1ef5b4d14 completed June 19, 2026, 6:43 a.m.
NEDg Description generation batch_6a34e5cf97c08190a6221df36b9d99fa completed June 19, 2026, 6:46 a.m.
NED2 Entity disambiguation (via description) batch_6a34e6d01ce08190b4edfcda322afae0 completed June 19, 2026, 6:50 a.m.
Created at: May 1, 2026, 1:25 a.m.