Triple
T8080740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Bulls |
E188606
|
entity |
| Predicate | sponsor |
P67
|
FINISHED |
| Object | Vodacom |
E350088
|
NE FINISHED |
How this triple was built (2 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 | Statement: [Blue Bulls, sponsor, Vodacom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vodacom Context triple: [Blue Bulls, sponsor, Vodacom]
-
A.
Vodacom
chosen
Vodacom is a major South African mobile communications company known for its extensive telecommunications services and prominent sports sponsorships.
-
B.
MTN Group
MTN Group is a South Africa-based multinational mobile telecommunications company operating across numerous countries in Africa and the Middle East.
-
C.
MTN
MTN is the stock ticker symbol for Vail Resorts, a major operator of ski resorts and mountain recreation properties.
-
D.
MTN
MTN is the IATA airport code for Martin State Airport, a public airport serving the Baltimore, Maryland area.
-
E.
Telenor
Telenor is a major Norwegian telecommunications company that provides mobile, broadband, and digital services across Scandinavia and multiple international markets.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca82b662e88190b9323daab8c28a21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb40a504d48190ace96e814d99b182 |
completed | March 31, 2026, 3:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc63fba1148190b8d0f04faa5330a1 |
completed | April 1, 2026, 12:16 a.m. |
Created at: March 30, 2026, 5:28 p.m.