Triple

T37932978
Position Surface form Disambiguated ID Type / Status
Subject Microsoft Defender E946265 entity
Predicate hasComponent P35 FINISHED
Object Microsoft Defender Application Guard
Microsoft Defender Application Guard is a security feature that isolates untrusted websites and documents in a hardware-based virtualized container to protect the host system from attacks.
E2249015 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: Microsoft Defender Application Guard | Statement: [Microsoft Defender, hasComponent, Microsoft Defender Application Guard]
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: Microsoft Defender Application Guard
Triple: [Microsoft Defender, hasComponent, Microsoft Defender Application Guard]
Generated description
Microsoft Defender Application Guard is a security feature that isolates untrusted websites and documents in a hardware-based virtualized container to protect the host system from attacks.

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_69f76ef3b7248190892fb9706423be7c completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbbd98a8d88190a5fcfaa901c5c80f completed May 6, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a410cdcff788190a68c9f3679647773 completed June 28, 2026, noon
NEDg Description generation batch_6a410e48cea88190bd5089907e6d2203 completed June 28, 2026, 12:06 p.m.
NED2 Entity disambiguation (via description) batch_6a41120678348190bb53bd1963a0ee5c completed June 28, 2026, 12:22 p.m.
Created at: May 3, 2026, 4:20 p.m.