Triple
T17515425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Risch |
E426554
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | ZG |
—
|
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: ZG | Statement: [Risch, vehicleRegistrationCode, ZG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ZG Context triple: [Risch, vehicleRegistrationCode, ZG]
-
A.
ZG
chosen
ZG is the vehicle registration code used on license plates for the city of Zagreb, the capital of Croatia.
-
B.
ZAG
ZAG is the three-letter IATA airport code for Zagreb Franjo Tuđman Airport, the main international airport serving Croatia’s capital city, Zagreb.
-
C.
ZAG
ZAG is the commonly used abbreviation for Zagłębie Lubin, a professional football club based in Lubin, Poland.
-
D.
ZGG
ZGG is the National Rail station code assigned to Gunnersbury railway station in London.
-
E.
DZG
DZG is the vehicle registration code assigned to cars registered in the Bogatynia area of 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_69d889dd9164819087b1dc3c9240c870 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4525fa0c48190b42b36c40db7ed7f |
completed | April 19, 2026, 3:56 a.m. |
Created at: April 10, 2026, 5:49 a.m.