Triple
T18949136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shenzhen University |
E463597
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | SZU |
—
|
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: SZU | Statement: [Shenzhen University, abbreviation, SZU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SZU Context triple: [Shenzhen University, abbreviation, SZU]
-
A.
SZU
chosen
SZU is the commonly used abbreviation for Shenzhen University, a comprehensive public university located in Shenzhen, China.
-
B.
SZF
SZF is the IATA airport code for Samsun-Çarşamba Airport, a regional airport serving the city of Samsun in northern Turkey.
-
C.
SZ
SZ is the official station code used to identify the Berlin U-Bahn station Seestraße.
-
D.
SZ
SZ is the vehicle registration code for the German city of Salzgitter in Lower Saxony.
-
E.
SZZ
SZZ is the three-letter IATA airport code for Szczecin-Goleniów Airport in northwestern Poland.
- 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_69d8dcfec90481909e926be9767e5779 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d541ef18819080b2e253dd23835d |
completed | April 20, 2026, 7:26 a.m. |
Created at: April 10, 2026, noon