Triple
T3473053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samsung SDS |
E73307
|
entity |
| Predicate | memberOf |
P10
|
FINISHED |
| Object | Samsung Group |
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 Group | Statement: [Samsung SDS, memberOf, Samsung Group]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samsung Group Context triple: [Samsung SDS, memberOf, Samsung Group]
-
A.
LG Corporation
LG Corporation is a major South Korean multinational conglomerate with diversified businesses spanning electronics, chemicals, and telecommunications.
-
B.
Samsung
chosen
Samsung is a South Korean multinational conglomerate best known globally for its smartphones, consumer electronics, and advanced semiconductor technologies.
-
C.
Samsung C&T
Samsung C&T is a South Korean construction and trading company known for executing major global projects, including landmark skyscrapers and large-scale infrastructure.
-
D.
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.
-
E.
Samsung Chaebol
Samsung Chaebol is a major South Korean conglomerate comprising numerous affiliated companies across industries such as electronics, shipbuilding, construction, and finance.
- 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_69ad85b2fed48190948c8765e453d270 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb3e03e081908aa09291bbf351bd |
completed | March 8, 2026, 6:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b54c2144708190a4a620222eeee5d3 |
completed | March 14, 2026, 11:53 a.m. |
Created at: March 8, 2026, 3:17 p.m.