Triple
T3095514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kitack Lim |
E64585
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Kitack Lim |
E64585
|
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: Kitack Lim | Statement: [Kitack Lim, name, Kitack Lim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kitack Lim Context triple: [Kitack Lim, name, Kitack Lim]
-
A.
Kitack Lim
chosen
Kitack Lim is a South Korean maritime administrator and diplomat who served as Secretary-General of the International Maritime Organization, the United Nations agency responsible for regulating global shipping.
-
B.
Do Ho Suh
Do Ho Suh is a South Korean contemporary artist known for his intricate sculptures and installations that explore themes of home, memory, and personal space.
-
C.
John Kim
John Kim is a prominent mechanical engineer and researcher renowned for his pioneering work in computational fluid dynamics and turbulence modeling.
-
D.
John Kim
John Kim is an Australian actor best known for his role as Ezekiel Jones in the fantasy-adventure television series "The Librarians."
-
E.
Kwanghun Chung
Kwanghun Chung is a neuroscientist and bioengineer known for pioneering advanced tissue-clearing and imaging techniques that enable high-resolution, three-dimensional visualization of biological tissues.
- 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_69ad857c97d88190b26f9b1c90839c77 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada23b04188190919a69987d2c180f |
completed | March 8, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20370aba48190a31ec25bca0a4727 |
completed | March 12, 2026, 12:06 a.m. |
Created at: March 8, 2026, 3:03 p.m.