Triple
T12928608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Rainicorn |
E309309
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object | Kim Kil Whan |
E1011121
|
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: Kim Kil Whan | Statement: [Lady Rainicorn, hasChild, Kim Kil Whan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kim Kil Whan Context triple: [Lady Rainicorn, hasChild, Kim Kil Whan]
-
A.
Kim Kil Whan
chosen
Kim Kil Whan is a responsible, business-minded Rainicorn-dog hybrid from Adventure Time who often contrasts with his carefree father, Jake the Dog.
-
B.
Kim Hong-gul
Kim Hong-gul is a South Korean politician and the son of former President and Nobel Peace Prize laureate Kim Dae-jung.
-
C.
Kim Jung-soo
Kim Jung-soo is a South Korean architect best known for designing the National Assembly Building in Seoul.
-
D.
Shim Joong-bo
Shim Joong-bo is a Catholic prelate known for having ordained Lázaro You Heung-sik, a prominent Korean cardinal in the Roman Catholic Church.
-
E.
Han Jin-won
Han Jin-won is a South Korean screenwriter best known for co-writing the Academy Award–winning film "Parasite."
- 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971ec72a48190aceef10630603d2c |
completed | April 10, 2026, 9:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6b8d58a0c8190b96252f04fdf1256 |
completed | May 3, 2026, 2:54 a.m. |
Created at: April 9, 2026, 5:42 p.m.