Triple

T33840816
Position Surface form Disambiguated ID Type / Status
Subject Abbott Diabetes Care E867353 entity
Predicate product P490 FINISHED
Object FreeStyle Lite blood glucose meter
The FreeStyle Lite blood glucose meter is a compact, easy-to-use blood sugar monitoring device designed by Abbott Diabetes Care for people managing diabetes.
E867353 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: FreeStyle Lite blood glucose meter | Statement: [Abbott Diabetes Care, product, FreeStyle Lite blood glucose meter]
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: FreeStyle Lite blood glucose meter
Triple: [Abbott Diabetes Care, product, FreeStyle Lite blood glucose meter]
Generated description
The FreeStyle Lite blood glucose meter is a compact, easy-to-use blood sugar monitoring device designed by Abbott Diabetes Care for people managing diabetes.

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_69f34992ad40819087760ed939bd2a7a completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f7004f4d9c8190b6517493f08084d4 completed May 3, 2026, 7:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a367611a0b481909ad2dc2081ef5c06 completed June 20, 2026, 11:14 a.m.
NEDg Description generation batch_6a3676bcd1c48190be60af977f59ab1c completed June 20, 2026, 11:17 a.m.
NED2 Entity disambiguation (via description) batch_6a367856f37c8190a4ff255c3590592e completed June 20, 2026, 11:24 a.m.
Created at: May 1, 2026, 1:47 a.m.