Triple
T14884635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vodacom |
E350088
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object |
Vodacom Tanzania
Vodacom Tanzania is a leading mobile network operator in Tanzania, providing voice, data, and mobile financial services as part of the broader Vodacom Group.
|
E350088
|
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: Vodacom Tanzania | Statement: [Vodacom, hasSubsidiary, Vodacom Tanzania]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vodacom Tanzania Context triple: [Vodacom, hasSubsidiary, Vodacom Tanzania]
-
A.
Vodacom
Vodacom is a major South African mobile communications company known for its extensive telecommunications services and prominent sports sponsorships.
-
B.
Econet Wireless
Econet Wireless is a major telecommunications company, originally founded in Zimbabwe, that provides mobile and related digital communication services across multiple African markets.
-
C.
MTN Group
MTN Group is a South Africa-based multinational mobile telecommunications company operating across numerous countries in Africa and the Middle East.
-
D.
MTN
MTN is the IATA airport code for Martin State Airport, a public airport serving the Baltimore, Maryland area.
-
E.
MTN
MTN is the stock ticker symbol for Vail Resorts, a major operator of ski resorts and mountain recreation properties.
- 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: Vodacom Tanzania Triple: [Vodacom, hasSubsidiary, Vodacom Tanzania]
Generated description
Vodacom Tanzania is a leading mobile network operator in Tanzania, providing voice, data, and mobile financial services as part of the broader Vodacom Group.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vodacom Tanzania Target entity description: Vodacom Tanzania is a leading mobile network operator in Tanzania, providing voice, data, and mobile financial services as part of the broader Vodacom Group.
-
A.
Vodacom
chosen
Vodacom is a major South African mobile communications company known for its extensive telecommunications services and prominent sports sponsorships.
-
B.
Econet Wireless
Econet Wireless is a major telecommunications company, originally founded in Zimbabwe, that provides mobile and related digital communication services across multiple African markets.
-
C.
MTN Group
MTN Group is a South Africa-based multinational mobile telecommunications company operating across numerous countries in Africa and the Middle East.
-
D.
MTN
MTN is the IATA airport code for Martin State Airport, a public airport serving the Baltimore, Maryland area.
-
E.
MTN
MTN is the stock ticker symbol for Vail Resorts, a major operator of ski resorts and mountain recreation properties.
- F. None of above.
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_69d822ee4f408190b6ac3b2fa434f0df |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5f4598081908735e8d7dfce8074 |
completed | April 15, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b5d0a208190b2490c86b15a42db |
completed | May 8, 2026, 11:01 p.m. |
| NEDg | Description generation | batch_69fe6c7cc6a481908b1b7e15cd7640a5 |
completed | May 8, 2026, 11:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe6e0950e481909c63e47bc98267bf |
completed | May 8, 2026, 11:13 p.m. |
Created at: April 10, 2026, 1:56 a.m.