Triple
T497967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samsung Pay |
E10335
|
entity |
| Predicate | owner |
P347
|
FINISHED |
| Object | Samsung Electronics |
E13776
|
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: Samsung Electronics | Statement: [Samsung Pay, owner, Samsung Electronics]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samsung Electronics Context triple: [Samsung Pay, owner, Samsung Electronics]
-
A.
Samsung
chosen
Samsung is a South Korean multinational conglomerate best known globally for its smartphones, consumer electronics, and advanced semiconductor technologies.
-
B.
LG Electronics
LG Electronics is a South Korean multinational electronics company known for producing a wide range of consumer electronics, home appliances, and mobile devices.
-
C.
Foxconn
Foxconn is a major Taiwanese multinational electronics manufacturer best known for assembling products for companies like Apple, including iPhones and other consumer devices.
-
D.
Huawei
Huawei is a major Chinese multinational technology company best known globally for its telecommunications equipment, smartphones, and role in 5G network infrastructure.
-
E.
Toshiba
Toshiba is a major Japanese multinational conglomerate known for its electronics, semiconductors, and information technology products and services.
- 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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1183e988190bce70932a9678134 |
completed | Feb. 28, 2026, 1:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a49eb7b49c819098352f36d020cde7 |
completed | March 1, 2026, 8:16 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.