Triple

T31819044
Position Surface form Disambiguated ID Type / Status
Subject VMware High Availability E812212 entity
Predicate hasFeature P182 FINISHED
Object VM Monitoring
VM Monitoring is a VMware High Availability feature that automatically detects and restarts virtual machines when their operating systems or VMware Tools become unresponsive.
E1977095 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: VM Monitoring | Statement: [VMware High Availability, hasFeature, VM Monitoring]
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: VM Monitoring
Triple: [VMware High Availability, hasFeature, VM Monitoring]
Generated description
VM Monitoring is a VMware High Availability feature that automatically detects and restarts virtual machines when their operating systems or VMware Tools become unresponsive.

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_69f348e97fa48190aa06286962af6dee completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6ad0a84108190b50c54bf97833c8b completed May 3, 2026, 2:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2d9d7372ec8190ad9419feb4512d8d completed June 13, 2026, 6:12 p.m.
NEDg Description generation batch_6a2d9e6d021481908201446811a134ef completed June 13, 2026, 6:16 p.m.
NED2 Entity disambiguation (via description) batch_6a2d9f0a0cf08190b4787d259334a31e completed June 13, 2026, 6:18 p.m.
Created at: April 30, 2026, 11:45 p.m.