Triple
T18572308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raffles Institution |
E453901
|
entity |
| Predicate | hasAlumnus |
P51
|
FINISHED |
| Object | Chao Tzee Cheng |
—
|
NE NERFINISHED |
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: Chao Tzee Cheng | Statement: [Raffles Institution, hasAlumnus, Chao Tzee Cheng]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chao Tzee Cheng Context triple: [Raffles Institution, hasAlumnus, Chao Tzee Cheng]
-
A.
Tzu Chiang
Tzu Chiang is the nickname of the AIDC AT-3, a Taiwanese advanced jet trainer and light attack aircraft.
-
B.
Ke Chieh
Ke Chieh is the Taiwanese romanization of Ke Jie, the Chinese professional Go player renowned for being one of the world's strongest and for his high-profile matches against AI programs like AlphaGo.
-
C.
Chih-chung
Chih-chung is an alternative romanization of the Chinese given name Zhizhong, used in older or non–pinyin transcription systems.
-
D.
Liang-Chieh Chen
Liang-Chieh Chen is a computer vision and deep learning researcher known for influential work on neural network architectures and efficient models such as MobileNetV2.
-
E.
Chao Tze-chi
chosen
Chao Tze-chi is an individual whose family name is Chao, likely of Chinese or Taiwanese origin.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53b032488819098de683bb5c42c4b |
completed | April 19, 2026, 8:28 p.m. |
Created at: April 10, 2026, 11:43 a.m.