Triple
T10989306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baku State University |
E259713
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | BSU |
E791362
|
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: BSU | Statement: [Baku State University, shortName, BSU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BSU Context triple: [Baku State University, shortName, BSU]
-
A.
BSU
BSU is the National Rail station code for Brunstane railway station in Edinburgh, Scotland.
-
B.
BSU
chosen
BSU is the commonly used abbreviation for Belarusian State University, a major public research university in Minsk, Belarus.
-
C.
BSU
BSU is the vehicle registration code assigned to the municipality of Filipów in Poland.
-
D.
LBSU
LBSU is the commonly used abbreviation for California State University, Long Beach, particularly in the context of its athletic programs.
-
E.
CSU
CSU is a conservative Christian-democratic political party operating exclusively in Bavaria and partnering federally with Germany’s Christian Democratic Union (CDU).
- 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_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d787b6d0b48190aaf959e2609d34e5 |
completed | April 9, 2026, 11:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e344f95ab88190bbce8f0eab0b2713 |
completed | April 18, 2026, 8:46 a.m. |
Created at: April 8, 2026, 9:24 p.m.