Triple
T11772278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yonsei–Korea sports rivalry |
E279928
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Yeon-Ko Jeon |
E945806
|
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: Yeon-Ko Jeon | Statement: [Yonsei–Korea sports rivalry, alsoKnownAs, Yeon-Ko Jeon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yeon-Ko Jeon Context triple: [Yonsei–Korea sports rivalry, alsoKnownAs, Yeon-Ko Jeon]
-
A.
Ko-Yeon Jeon
chosen
Ko-Yeon Jeon is the traditional and highly anticipated annual sports rivalry event between Yonsei University and Korea University in South Korea.
-
B.
Myung-wha Chung
Myung-wha Chung is a renowned South Korean cellist recognized for her international concert career and collaborations with major orchestras and chamber ensembles.
-
C.
Ji-hyun Jung
Ji-hyun Jung is a Korean given name borne by various notable individuals, including figures in entertainment, sports, and other public fields.
-
D.
Da-yeon Jung
Da-yeon Jung is a Korean individual notable enough to be recognized as a prominent bearer of the surname Jung.
-
E.
Soo-Yung Han
Soo-Yung Han is the young daughter of a Chinese consul whose kidnapping repeatedly drives the central plot and emotional stakes of the Rush Hour film series.
- 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_69d6ab01d2688190ad8ed6bda487eaa5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a55dfa088190a59b35d0247225e3 |
completed | April 10, 2026, 7:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f130b45ce081908669f4287961da7c |
completed | April 28, 2026, 10:12 p.m. |
Created at: April 8, 2026, 9:41 p.m.