Powerset
E697368
Powerset was a natural-language search engine startup, later acquired by Microsoft, that focused on enabling more intuitive, semantic web search.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Powerset canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T7893286 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Powerset Context triple: [Tom Preston-Werner, workedAt, Powerset]
-
A.
SETS
SETS is the London Stock Exchange’s central electronic order book system used for automated trading of the most liquid UK securities.
-
B.
POWER2
POWER2 is a second-generation IBM RISC microprocessor architecture designed to deliver high-performance computing, particularly for scientific and technical workloads.
-
C.
NSSet
NSSet is an Objective-C collection class that represents an unordered, unique set of objects, commonly used in Cocoa and Cocoa Touch frameworks.
-
D.
POWER1
POWER1 is IBM’s first-generation 32-bit RISC microprocessor architecture used in early RS/6000 workstations and servers.
-
E.
Set
Set is an ancient Egyptian god associated primarily with chaos, storms, and disorder, often depicted as the adversary of his brother Osiris and the rival of Horus.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Powerset Target entity description: Powerset was a natural-language search engine startup, later acquired by Microsoft, that focused on enabling more intuitive, semantic web search.
-
A.
SETS
SETS is the London Stock Exchange’s central electronic order book system used for automated trading of the most liquid UK securities.
-
B.
POWER2
POWER2 is a second-generation IBM RISC microprocessor architecture designed to deliver high-performance computing, particularly for scientific and technical workloads.
-
C.
NSSet
NSSet is an Objective-C collection class that represents an unordered, unique set of objects, commonly used in Cocoa and Cocoa Touch frameworks.
-
D.
POWER1
POWER1 is IBM’s first-generation 32-bit RISC microprocessor architecture used in early RS/6000 workstations and servers.
-
E.
Set
Set is an ancient Egyptian god associated primarily with chaos, storms, and disorder, often depicted as the adversary of his brother Osiris and the rival of Horus.
- F. None of above. chosen
Statements (29)
| Predicate | Object |
|---|---|
| instanceOf |
natural-language search engine
ⓘ
search engine company ⓘ technology company ⓘ |
| acquiredBy | Microsoft NERFINISHED ⓘ |
| acquisitionDate | 2008 ⓘ |
| acquisitionStatus | acquired ⓘ |
| basedIn |
California, United States
ⓘ
surface form:
California
San Francisco NERFINISHED ⓘ United States of America ⓘ
surface form:
United States
|
| businessModel | web-based service ⓘ |
| contributedTechnologyTo | Microsoft search products NERFINISHED ⓘ |
| contributedTo | Bing NERFINISHED ⓘ |
| country |
United States of America
ⓘ
surface form:
United States
|
| focus |
intuitive web search
ⓘ
natural-language search ⓘ semantic search ⓘ |
| goal |
enable more intuitive web search
ⓘ
extract meaning from web pages ⓘ understand user queries in natural language ⓘ |
| industry |
information technology
ⓘ
natural language processing ⓘ web search ⓘ |
| notableFor |
natural-language interface to search
ⓘ
semantic web search approach ⓘ |
| parentCompanyAfterAcquisition | Microsoft NERFINISHED ⓘ |
| technologyUsed |
linguistic parsing
ⓘ
natural language processing ⓘ semantic analysis ⓘ |
| webDomainType | search engine ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Powerset Description of subject: Powerset was a natural-language search engine startup, later acquired by Microsoft, that focused on enabling more intuitive, semantic web search.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.