Triple
T7588840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sun Fo |
E179683
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ke |
E349933
|
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: Ke | Statement: [Sun Fo, givenName, Ke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ke Context triple: [Sun Fo, givenName, Ke]
-
A.
Ke
chosen
Ke is the given name of Ke Huy Quan, the Vietnamese-American actor and former child star known for roles in films like "Indiana Jones and the Temple of Doom," "The Goonies," and "Everything Everywhere All at Once."
-
B.
Ka
Ka is the introspective poet and protagonist of Orhan Pamuk’s novel "Snow," whose return to Turkey and entanglement in political and personal conflicts drive the story’s exploration of faith, identity, and modernity.
-
C.
Ka
Ka was an early ancient Egyptian king of the First Dynasty period, known from tomb inscriptions at Abydos and considered one of the first rulers to use a royal serekh.
-
D.
Kar
Kar is the young, streetwise pickpocket chosen as the reluctant successor to a mystical protector in the action film "Bulletproof Monk."
-
E.
KE
KE is the IATA airline designator for Korean Air, the flag carrier and largest airline of South Korea.
- 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_69c69f335248819093c1006f30513708 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f99991948190af1fb0635895ad94 |
completed | March 27, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8618d29c4819083e78266af8f2daa |
completed | March 28, 2026, 11:17 p.m. |
Created at: March 27, 2026, 3:52 p.m.