Triple
T8903639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southwest University of Finance and Economics |
E211991
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
SWUFE
SWUFE is a leading Chinese university specializing in finance, economics, and business education and research.
|
E766502
|
NE FINISHED |
How this triple was built (4 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: SWUFE | Statement: [Southwest University of Finance and Economics, shortName, SWUFE]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SWUFE Context triple: [Southwest University of Finance and Economics, shortName, SWUFE]
-
A.
SCUT
SCUT is a major public research university in Guangzhou, China, known for its strong engineering, technology, and applied science programs.
-
B.
SCAU
SCAU is a French architectural firm known for designing major public and sports facilities, including the redevelopment of Marseille’s Stade Vélodrome.
-
C.
Weifang University
Weifang University is a comprehensive higher education institution located in the city of Weifang in Shandong Province, China.
-
D.
NUAA
NUAA is a leading Chinese university in Nanjing specializing in aeronautics, astronautics, and engineering disciplines.
-
E.
Central South University
Central South University is a major comprehensive research university in Changsha, Hunan, China, known for its strong engineering, medical, and materials science programs.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: SWUFE Triple: [Southwest University of Finance and Economics, shortName, SWUFE]
Generated description
SWUFE is a leading Chinese university specializing in finance, economics, and business education and research.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SWUFE Target entity description: SWUFE is a leading Chinese university specializing in finance, economics, and business education and research.
-
A.
SCUT
SCUT is a major public research university in Guangzhou, China, known for its strong engineering, technology, and applied science programs.
-
B.
SCAU
SCAU is a French architectural firm known for designing major public and sports facilities, including the redevelopment of Marseille’s Stade Vélodrome.
-
C.
Weifang University
Weifang University is a comprehensive higher education institution located in the city of Weifang in Shandong Province, China.
-
D.
NUAA
NUAA is a leading Chinese university in Nanjing specializing in aeronautics, astronautics, and engineering disciplines.
-
E.
Central South University
Central South University is a major comprehensive research university in Changsha, Hunan, China, known for its strong engineering, medical, and materials science programs.
- F. None of above. chosen
Provenance (5 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_69ca839255248190b43984294abd92ae |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc64c091d08190b59e54eb4a184e41 |
completed | April 1, 2026, 12:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfba26bc7881908639e9a812dec894 |
completed | April 3, 2026, 1:01 p.m. |
| NEDg | Description generation | batch_69cfbcab0cd88190a2ea89e27324e4ff |
completed | April 3, 2026, 1:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfbd71b8ec81909d222897c898e78a |
completed | April 3, 2026, 1:15 p.m. |
Created at: March 30, 2026, 6:55 p.m.