Triple
T14933889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olsztyn |
E372338
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | NOL |
E783892
|
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: NOL | Statement: [Olsztyn, vehicleRegistrationCode, NOL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NOL Context triple: [Olsztyn, vehicleRegistrationCode, NOL]
-
A.
NOL
NOL is the Amtrak station code for New Orleans’ main intercity rail hub, the New Orleans Union Passenger Terminal.
-
B.
NOL
chosen
NOL is a Polish vehicle registration code assigned to cars registered in the Olsztyn County area, which includes the town of Jeziorany.
-
C.
Nol
Nol is the given name of Lon Nol, the Cambodian military leader and politician who served as Prime Minister and later led the Khmer Republic in the early 1970s.
-
D.
NUOL
NUOL is the principal public university in Laos, offering a wide range of higher education and research programs across multiple disciplines.
-
E.
NOB
NOB is the abbreviation for Dutch National Opera & Ballet, the leading institution for opera and ballet performances in the Netherlands.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded646a0808190ba5c0c91bde011c5 |
completed | April 15, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe7e8c8d188190b027f14256b0ce01 |
completed | May 9, 2026, 12:23 a.m. |
Created at: April 10, 2026, 2:37 a.m.