Triple
T8482276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lee Sedol |
E200548
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Lee Sedol |
E200548
|
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: Lee Sedol | Statement: [Lee Sedol, name, Lee Sedol]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lee Sedol Context triple: [Lee Sedol, name, Lee Sedol]
-
A.
Lee Sedol
chosen
Lee Sedol is a South Korean professional Go player renowned as one of the strongest players in history and for his landmark 2016 match against DeepMind's AlphaGo.
-
B.
Ke Jie
Ke Jie is a Chinese professional Go player widely regarded as one of the strongest players of his generation.
-
C.
Sung-kyu Jung
Sung-kyu Jung is a notable individual recognized as a prominent bearer of the Korean surname Jung.
-
D.
Chan-sung Jung
Chan-sung Jung, widely known as "The Korean Zombie," is a South Korean mixed martial artist recognized for his exciting fighting style and success in top MMA promotions like the UFC.
-
E.
Eui-Sung Yi
Eui-Sung Yi is a prominent architect and urban designer known for his leadership role at the innovative architecture firm Morphosis.
- 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_69ca831b17988190a1f3f3413d57b820 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe53638c48190b742fc51d1b4442a |
completed | March 31, 2026, 3:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce3a2b2e9081909f19712946c6ec20 |
completed | April 2, 2026, 9:43 a.m. |
Created at: March 30, 2026, 6:12 p.m.