Triple
T7384560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nanjing University |
E170348
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object | 南京大学 |
E170348
|
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: 南京大学 | Statement: [Nanjing University, nativeName, 南京大学]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 南京大学 Context triple: [Nanjing University, nativeName, 南京大学]
-
A.
南开大学
南开大学 is a prestigious comprehensive research university in Tianjin, China, renowned for its strong academic tradition and influential alumni.
-
B.
Nanjing Normal University
Nanjing Normal University is a comprehensive public university in Nanjing, China, known for its strong teacher education programs and broad range of disciplines.
-
C.
Nanjing University
chosen
Nanjing University is one of China’s oldest and most prestigious research universities, renowned for its strong academic programs and historical significance.
-
D.
Southeast University
Southeast University is a major public research university in Nanjing, China, known for its strong engineering, architecture, and technology programs.
-
E.
Soochow University
Soochow University is a major comprehensive research university in Suzhou, China, known for its strong programs in humanities, social sciences, and engineering.
- 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_69c68a5d0ed08190b6d361e68f813330 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f1efe1308190b96eefbff56140be |
completed | March 27, 2026, 9:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c802e23714819094a1b31c82a27fee |
completed | March 28, 2026, 4:33 p.m. |
Created at: March 27, 2026, 3:08 p.m.