Triple
T9643335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SK hynix |
E233128
|
entity |
| Predicate | isPartOf |
P10
|
FINISHED |
| Object | KOSPI index |
E356386
|
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: KOSPI index | Statement: [SK hynix, isPartOf, KOSPI index]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KOSPI index Context triple: [SK hynix, isPartOf, KOSPI index]
-
A.
KOSPI
chosen
KOSPI is South Korea’s main stock market index, tracking the performance of large companies listed on the Korea Exchange.
-
B.
Korea Exchange (KRX)
Korea Exchange (KRX) is South Korea’s main securities and derivatives exchange, providing a centralized marketplace for trading stocks, bonds, derivatives, and other financial instruments.
-
C.
KSE-100 Index
The KSE-100 Index is Pakistan’s benchmark stock market index, tracking the performance of the largest and most liquid companies listed on the Pakistan Stock Exchange.
-
D.
SSE Composite Index
The SSE Composite Index is a major Chinese stock market index that tracks the performance of all stocks listed on the Shanghai Stock Exchange.
-
E.
KOSDAQ Market
KOSDAQ Market is South Korea’s secondary stock market, specializing in the listing and trading of small and medium-sized growth and technology companies.
- 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_69ca848a5a908190aad251f4137b0c3a |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9b7e2c488190b0f0dfa6d82618c8 |
completed | April 1, 2026, 10:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d18a00a87081909d1e59aa7192a69c |
completed | April 4, 2026, 10 p.m. |
Created at: March 30, 2026, 8:12 p.m.