Triple
T16904377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koo Cha-kyung |
E424520
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | LG Group |
—
|
NE NERFINISHED |
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: LG Group | Statement: [Koo Cha-kyung, employer, LG Group]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LG Group Context triple: [Koo Cha-kyung, employer, LG Group]
-
A.
LG Group
chosen
LG Group is a major South Korean multinational conglomerate known for its electronics, chemicals, and telecommunications businesses.
-
B.
Hyundai Motor Group
Hyundai Motor Group is a South Korean multinational conglomerate primarily known for its global automotive operations, including the Hyundai and Kia brands, along with various affiliated mobility and manufacturing businesses.
-
C.
Hyundai Motor Company
Hyundai Motor Company is a leading South Korean automotive manufacturer known globally for producing a wide range of affordable and reliable vehicles.
-
D.
Hyundai Group (historically)
Hyundai Group (historically) was a major South Korean chaebol conglomerate with diversified interests spanning construction, shipbuilding, automotive, and heavy industries.
-
E.
Kia Motors
Kia Motors is a South Korean automobile manufacturer known for producing a wide range of affordable cars and SUVs for global markets.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889da3e8c8190a2b118f383f0beac |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3c8df454c8190898ebdd75985e51c |
completed | April 18, 2026, 6:09 p.m. |
Created at: April 10, 2026, 5:30 a.m.