TW
E367686
TW is the stock ticker symbol for Towers Watson, a global professional services firm specializing in risk management, insurance brokerage, and human resources consulting.
All labels observed (1)
| Label | Occurrences |
|---|---|
| TW canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T3535185 — 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: TW Context triple: [Towers Watson, tickerSymbol, TW]
-
A.
TW
TW is the two-letter ISO 3166 country code assigned to Taiwan (commonly referred to as Chinese Taipei in certain international contexts).
-
B.
TW
TW is a UK postcode area in southwest London and parts of Surrey, covering towns such as Twickenham and Staines-upon-Thames.
-
C.
TR
TR is the two-letter ISO 3166-1 alpha-2 country code assigned to Turkey for international standardization and referencing.
-
D.
TOR
TOR is the standard three-letter abbreviation used to represent the Toronto Maple Leafs in sports standings, statistics, and media.
-
E.
TOR
TOR is the official code designation used for the Georgian football club FC Torpedo Kutaisi.
- 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: TW Target entity description: TW is the stock ticker symbol for Towers Watson, a global professional services firm specializing in risk management, insurance brokerage, and human resources consulting.
-
A.
TW
TW is the two-letter ISO 3166 country code assigned to Taiwan (commonly referred to as Chinese Taipei in certain international contexts).
-
B.
TW
TW is a UK postcode area in southwest London and parts of Surrey, covering towns such as Twickenham and Staines-upon-Thames.
-
C.
TR
TR is the two-letter ISO 3166-1 alpha-2 country code assigned to Turkey for international standardization and referencing.
-
D.
TOR
TOR is the standard three-letter abbreviation used to represent the Toronto Maple Leafs in sports standings, statistics, and media.
-
E.
TOR
TOR is the official code designation used for the Georgian football club FC Torpedo Kutaisi.
- F. None of above. chosen
Statements (30)
| Predicate | Object |
|---|---|
| instanceOf |
company
ⓘ
professional services firm ⓘ stock ticker symbol ⓘ |
| areaServed | worldwide ⓘ |
| clientType |
corporations
ⓘ
governments ⓘ institutions ⓘ |
| country |
United States
ⓘ
linked to:
United States of America
|
| exchange | NYSE ⓘ |
| formerName |
Towers Watson & Co.
ⓘ
linked to:
Towers Watson
|
| hasService |
actuarial consulting
ⓘ
benefits consulting ⓘ insurance and reinsurance brokerage ⓘ risk and financial services ⓘ talent and rewards consulting ⓘ |
| headquartersLocation |
Arlington, Virginia, United States
ⓘ
linked to:
Arlington, Virginia
|
| industry |
human resources consulting
ⓘ
insurance brokerage ⓘ professional services ⓘ |
| language | English (primary business language) ⓘ |
| listedOn | New York Stock Exchange ⓘ |
| represents | Towers Watson ⓘ |
| resultedFrom | merger of Towers Perrin and Watson Wyatt Worldwide ⓘ |
| scope | global ⓘ |
| specializesIn |
human resources consulting
ⓘ
insurance brokerage ⓘ risk management ⓘ |
| successor |
Willis Towers Watson
ⓘ
linked to:
Towers Watson
|
| successorTicker | WLTW ⓘ |
| tradedAs | TW ⓘ |
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: TW Description of subject: TW is the stock ticker symbol for Towers Watson, a global professional services firm specializing in risk management, insurance brokerage, and human resources consulting.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.