Triple
T23527393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beijing Normal University |
E576469
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | BNU |
—
|
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: BNU | Statement: [Beijing Normal University, shortName, BNU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BNU Context triple: [Beijing Normal University, shortName, BNU]
-
A.
BNU
chosen
BNU is a modern British public university in High Wycombe, Buckinghamshire, known for its career-focused courses and strong links with industry and the creative sectors.
-
B.
PNU
PNU is the Philippine Normal University, a premier state institution in the Philippines specializing in teacher education and training.
-
C.
PNU
PNU is a major national research university located in Busan, South Korea, known for its comprehensive academic programs and strong regional influence.
-
D.
NSU
NSU is a private research university in Fort Lauderdale, Florida, known for its programs in health professions, law, business, and education.
-
E.
NSU
NSU is a leading Russian research university located in Novosibirsk, known for its strong programs in science, technology, and mathematics.
- 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_69e245f5a8848190a2ba42e271c6c31f |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1ac74be1881909161b94aa611188a |
completed | April 29, 2026, 7 a.m. |
Created at: April 17, 2026, 6:09 p.m.