Triple
T6931172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KDDI |
E160435
|
entity |
| Predicate | competitor |
P1375
|
FINISHED |
| Object | NTT Docomo |
E123439
|
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: NTT Docomo | Statement: [KDDI, competitor, NTT Docomo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NTT Docomo Context triple: [KDDI, competitor, NTT Docomo]
-
A.
NTT DoCoMo
chosen
NTT DoCoMo is Japan’s largest mobile network operator, known for pioneering advanced mobile technologies and services, including early 3G deployments.
-
B.
SoftBank Group
SoftBank Group is a Japanese multinational conglomerate holding company best known for its large-scale technology investments and telecommunications businesses.
-
C.
KDDI
KDDI is a major Japanese telecommunications company that provides mobile, broadband, and other communication services domestically and internationally.
-
D.
Tokyo Tsushin Kogyo
Tokyo Tsushin Kogyo was the original name of the Japanese electronics company that later became globally known as Sony.
-
E.
Fujitsu Limited
Fujitsu Limited is a major Japanese multinational information and communications technology company known for its computing products, IT services, and solutions.
- 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_69c6884e15208190b9e91487eaafcf85 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6da3e58f08190857c14f538448039 |
completed | March 27, 2026, 7:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7514b0dd8819097a3fa1a38c913f4 |
completed | March 28, 2026, 3:55 a.m. |
Created at: March 27, 2026, 2:27 p.m.