Triple

T27850975
Position Surface form Disambiguated ID Type / Status
Subject DAO E703950 entity
Predicate typicalEnvironment P12230 FINISHED
Object Microsoft Office solutions
Microsoft Office solutions are a suite of productivity applications and tools from Microsoft, such as Word, Excel, and PowerPoint, designed to support document creation, data analysis, communication, and collaboration in business and personal environments.
 E192462 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 Office solutions | Statement: [DAO, typicalEnvironment, Microsoft Office solutions]
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 Office solutions
Triple: [DAO, typicalEnvironment, Microsoft Office solutions]
Generated description
Microsoft Office solutions are a suite of productivity applications and tools from Microsoft, such as Word, Excel, and PowerPoint, designed to support document creation, data analysis, communication, and collaboration in business and personal 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_69ef840e614c8190a88cf9638c14a265 completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f63904eca48190b2471e80df98e1d2 completed May 2, 2026, 5:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12f73bbb688190b26d9a718a494201 completed May 24, 2026, 1:03 p.m.
NEDg Description generation batch_6a12fb4a4a808190bc0821b2bc754da0 completed May 24, 2026, 1:21 p.m.
NED2 Entity disambiguation (via description) batch_6a12fd21fb2c8190b52459bd901c05a0 completed May 24, 2026, 1:29 p.m.
Created at: April 27, 2026, 6:10 p.m.