Triple
T14894932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Telenet Group |
E359846
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object | Telenet |
E359846
|
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: Telenet | Statement: [Telenet Group, brand, Telenet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Telenet Context triple: [Telenet Group, brand, Telenet]
-
A.
Telenet Group
chosen
Telenet Group is a major Belgian telecommunications and entertainment provider offering services such as broadband internet, television, and mobile telephony.
-
B.
KPN
KPN is the abbreviation commonly used for the Korean People's Navy, the maritime branch of North Korea's armed forces.
-
C.
Deutsche Telekom
Deutsche Telekom is a major German telecommunications company and one of the largest telecom providers in Europe, offering mobile, fixed-line, and internet services worldwide.
-
D.
Ziggo
Ziggo is a major Dutch cable operator and telecommunications company providing television, internet, and phone services.
-
E.
Magyar Telekom
Magyar Telekom is Hungary’s leading telecommunications provider, offering mobile, fixed-line, and internet services as part of the Deutsche Telekom group.
- 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_69d827980cbc8190a0c569ae3940a1d9 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69ded6070b248190be8f4f91a0c0b1f3 |
completed | April 15, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b679fb081908cf8f41acfba3b99 |
completed | May 8, 2026, 11:01 p.m. |
Created at: April 10, 2026, 2:10 a.m.