Triple
T17351665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yuh Nung Jan |
E421826
|
entity |
| Predicate | notableStudent |
P4838
|
FINISHED |
| Object | Liqun Luo |
E1263211
|
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: Liqun Luo | Statement: [Yuh Nung Jan, notableStudent, Liqun Luo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Liqun Luo Context triple: [Yuh Nung Jan, notableStudent, Liqun Luo]
-
A.
Liqun Luo
chosen
Liqun Luo is a prominent neuroscientist known for his work on neural circuit assembly and function, particularly using Drosophila and mouse models.
-
B.
Zhen Luo
Zhen Luo, better known as Empress Zhen of Wei, was a consort of Cao Pi and posthumous empress of the state of Cao Wei during China’s Three Kingdoms period.
-
C.
Congrong Lu
Congrong Lu is the Chinese title of the classic Zen Buddhist koan collection known in English as the Book of Serenity.
-
D.
Yiliang Peng
Yiliang Peng, better known as Doublelift, is a retired professional League of Legends AD carry from North America renowned for his multiple LCS titles and status as one of the region’s greatest players.
-
E.
Tingye Li
Tingye Li was a pioneering Chinese-American optical engineer and physicist renowned for his foundational contributions to laser and fiber-optic communications.
- 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_69d889d520008190a26917a95bf1c2ea |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a2ca0708190aae8306ec3a6f2a7 |
completed | April 19, 2026, 2:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0195585e5881909b0ad386b65112ba |
completed | May 11, 2026, 8:37 a.m. |
Created at: April 10, 2026, 5:44 a.m.