Triple
T7001189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Internet in Poland |
E162339
|
entity |
| Predicate | majorISP |
P35275
|
FINISHED |
| Object | T-Mobile Polska |
E264711
|
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: T-Mobile Polska | Statement: [Internet in Poland, majorISP, T-Mobile Polska]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T-Mobile Polska Context triple: [Internet in Poland, majorISP, T-Mobile Polska]
-
A.
T-Mobile US
T-Mobile US is a major American wireless network operator known for its nationwide mobile phone services and aggressive “Un-carrier” marketing strategy.
-
B.
Telenor
Telenor is a major Norwegian telecommunications company that provides mobile, broadband, and digital services across Scandinavia and multiple international markets.
-
C.
Deutsche Telekom
chosen
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.
Telico
Telico is a small unincorporated community located in Ellis County, Texas.
-
E.
Telkom
Telkom is a major South African telecommunications company that provides fixed-line, mobile, and data services across the country.
- 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_69c68857ffc08190857dc62cd5253777 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e1d144648190b7e6558246b013e3 |
completed | March 27, 2026, 8 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c76a310eb08190a0fc1de2814aea08 |
completed | March 28, 2026, 5:42 a.m. |
Created at: March 27, 2026, 2:33 p.m.