Triple
T15135367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Internet in Nepal |
E361539
|
entity |
| Predicate | majorMobileOperator |
P84231
|
FINISHED |
| Object |
Smart Telecom
Smart Telecom is a Nepalese telecommunications company that operates as one of the country’s major mobile network providers.
|
E1138659
|
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: Smart Telecom | Statement: [Internet in Nepal, majorMobileOperator, Smart Telecom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Smart Telecom Context triple: [Internet in Nepal, majorMobileOperator, Smart Telecom]
-
A.
Smart Communications
Smart Communications is a major Philippine telecommunications company providing mobile, internet, and digital communication services nationwide.
-
B.
TELCO
TELCO is the former name and widely recognized abbreviation of Tata Motors, one of India’s largest automotive manufacturing companies.
-
C.
Telico
Telico is a small unincorporated community located in Ellis County, Texas.
-
D.
Mobile Co.
Mobile Co. is the standard abbreviation used to refer to Mobile County, a county located in the southwestern part of the U.S. state of Alabama.
-
E.
Sogetel
Sogetel is a film and television production company known for producing European, particularly French-language, cinematic works.
- 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: Smart Telecom Triple: [Internet in Nepal, majorMobileOperator, Smart Telecom]
Generated description
Smart Telecom is a Nepalese telecommunications company that operates as one of the country’s major mobile network providers.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Smart Telecom Target entity description: Smart Telecom is a Nepalese telecommunications company that operates as one of the country’s major mobile network providers.
-
A.
Smart Communications
Smart Communications is a major Philippine telecommunications company providing mobile, internet, and digital communication services nationwide.
-
B.
TELCO
TELCO is the former name and widely recognized abbreviation of Tata Motors, one of India’s largest automotive manufacturing companies.
-
C.
Telico
Telico is a small unincorporated community located in Ellis County, Texas.
-
D.
Mobile Co.
Mobile Co. is the standard abbreviation used to refer to Mobile County, a county located in the southwestern part of the U.S. state of Alabama.
-
E.
Sogetel
Sogetel is a film and television production company known for producing European, particularly French-language, cinematic works.
- 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_69d85a06450081909c5a14ea9851a15e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005b3f6f48190b1ed7c7b28feb7a6 |
completed | April 15, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feb7fe60488190bea566eaa3ebb47a |
completed | May 9, 2026, 4:28 a.m. |
| NEDg | Description generation | batch_69feb9d8f36081909afe0ad1f4518d58 |
completed | May 9, 2026, 4:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69feba3ff2c8819099cc5be8c556d526 |
completed | May 9, 2026, 4:38 a.m. |
Created at: April 10, 2026, 3:07 a.m.