Triple
T12544009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Professional Web |
E299913
|
entity |
| Predicate | abbreviationFor |
P43
|
FINISHED |
| Object |
PW
PW is the abbreviation for "The Professional Web," a term typically referring to the ecosystem of standards, tools, and practices used to build and maintain modern, production-quality websites and web applications.
|
E988825
|
NE FINISHED |
How this triple was built (4 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: PW | Statement: [The Professional Web, abbreviationFor, PW]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PW Context triple: [The Professional Web, abbreviationFor, PW]
-
A.
PW
PW is the commonly used nickname of P. W. Botha, the former South African prime minister and state president during the apartheid era.
-
B.
PW
PW is the commonly used abbreviation for the Warsaw University of Technology, one of Poland’s leading technical universities.
-
C.
PW
PW is the ISO 3166-1 alpha-2 country code for the Pacific island nation of Palau.
-
D.
PW
PW is the abbreviated name for Price Waterhouse, a former major international accounting and professional services firm that later became part of PricewaterhouseCoopers (PwC).
-
E.
PJ
PJ is the common abbreviation for Petaling Jaya, a major city in the state of Selangor, Malaysia, known for its residential suburbs and commercial centers.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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: PW Triple: [The Professional Web, abbreviationFor, PW]
Generated description
PW is the abbreviation for "The Professional Web," a term typically referring to the ecosystem of standards, tools, and practices used to build and maintain modern, production-quality websites and web applications.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: PW Target entity description: PW is the abbreviation for "The Professional Web," a term typically referring to the ecosystem of standards, tools, and practices used to build and maintain modern, production-quality websites and web applications.
-
A.
PW
PW is the commonly used nickname of P. W. Botha, the former South African prime minister and state president during the apartheid era.
-
B.
PW
PW is the commonly used abbreviation for the Warsaw University of Technology, one of Poland’s leading technical universities.
-
C.
PW
PW is the ISO 3166-1 alpha-2 country code for the Pacific island nation of Palau.
-
D.
PW
PW is the abbreviated name for Price Waterhouse, a former major international accounting and professional services firm that later became part of PricewaterhouseCoopers (PwC).
-
E.
PJ
PJ is the common abbreviation for Petaling Jaya, a major city in the state of Selangor, Malaysia, known for its residential suburbs and commercial centers.
- F. None of above. chosen
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_69d6ada707008190aaec1238117c9379 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9547d6df4819080db8415d386ed38 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f655801cac8190b1f9a72f8fed0399 |
completed | May 2, 2026, 7:50 p.m. |
| NEDg | Description generation | batch_69f6566f40c08190baec227fb660c948 |
completed | May 2, 2026, 7:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f657aec8fc8190b3b08ccb95595958 |
completed | May 2, 2026, 7:59 p.m. |
Created at: April 8, 2026, 9:57 p.m.