Triple
T15171495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SEMCO |
E362495
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Samsung Group |
E1010375
|
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: [SEMCO, partOf, Samsung Group]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samsung Group Context triple: [SEMCO, partOf, Samsung Group]
-
A.
Samsung Group
chosen
Samsung Group is a South Korean multinational conglomerate best known globally for its consumer electronics, particularly smartphones, tablets, and televisions, as well as its significant presence in semiconductors and other industries.
-
B.
LG Corporation
LG Corporation is a major South Korean multinational conglomerate with diversified businesses spanning electronics, chemicals, and telecommunications.
-
C.
Hanwha Group
Hanwha Group is a major South Korean conglomerate with diversified businesses spanning chemicals, energy, defense, finance, and construction.
-
D.
SK Group
SK Group is one of South Korea’s largest conglomerates, with diversified businesses spanning energy, telecommunications, semiconductors, and chemicals.
-
E.
LG Group
LG Group is a major South Korean multinational conglomerate known for its electronics, chemicals, and telecommunications businesses.
- 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_69d85a087b7c81908baa94a53dac8d68 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0064ec56481909f11fa6e5686f076 |
completed | April 15, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feef66b4f08190a072332123253166 |
completed | May 9, 2026, 8:25 a.m. |
Created at: April 10, 2026, 3:08 a.m.