Triple
T6563735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SK Energy |
E153848
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | SK Group |
E605533
|
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: SK Group | Statement: [SK Energy, partOf, SK Group]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SK Group Context triple: [SK Energy, partOf, SK Group]
-
A.
SK Group
chosen
SK Group is one of South Korea’s largest conglomerates, with diversified businesses spanning energy, telecommunications, semiconductors, and chemicals.
-
B.
Hanwha Group
Hanwha Group is a major South Korean conglomerate with diversified businesses spanning chemicals, energy, defense, finance, and construction.
-
C.
POSCO Holdings
POSCO Holdings is a South Korean multinational steelmaking and materials conglomerate that serves as the holding company of the POSCO group, one of the world’s largest steel producers.
-
D.
Hanwha Engineering & Construction
Hanwha Engineering & Construction is a South Korean construction and engineering company known for undertaking large-scale international projects, including major stadiums and infrastructure developments.
-
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_69c6880cb35881909b763eb0125236b9 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ae3a40488190892d20ca0d60b937 |
completed | March 27, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6e42523848190b02682e6a640ac05 |
completed | March 27, 2026, 8:10 p.m. |
Created at: March 27, 2026, 1:52 p.m.