Triple
T15834189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CPNG |
E383944
|
entity |
| Predicate | tickerFor |
P9230
|
FINISHED |
| Object | Coupang, Inc. |
E79665
|
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: Coupang, Inc. | Statement: [CPNG, tickerFor, Coupang, Inc.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Coupang, Inc. Context triple: [CPNG, tickerFor, Coupang, Inc.]
-
A.
Coupang
chosen
Coupang is a South Korean e-commerce company often called the “Amazon of Korea,” known for its ultra-fast delivery service and dominant online retail platform.
-
B.
Coupang Eats
Coupang Eats is a South Korean food delivery platform operated by e-commerce giant Coupang, offering on-demand meal ordering from local restaurants.
-
C.
Shinsegae Group
Shinsegae Group is a major South Korean retail conglomerate best known for its department stores, supermarkets, and diverse consumer-focused businesses.
-
D.
Naver Corporation
Naver Corporation is a South Korean internet technology company best known for operating the Naver search engine and various online services and platforms.
-
E.
Lotte Group
Lotte Group is a major South Korean-Japanese multinational conglomerate with diverse businesses spanning food, retail, tourism, chemicals, and entertainment.
- 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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e11e6670d48190a456581dd951f168 |
completed | April 16, 2026, 5:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe69332c81909aa57e64de163cbe |
completed | May 9, 2026, 11:08 p.m. |
Created at: April 10, 2026, 4:49 a.m.