Triple
T3259776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Viterbo |
E68380
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
VT
VT is the vehicle registration code used on license plates for vehicles registered in the Province of Viterbo in Italy.
|
E341703
|
NE FINISHED |
How this triple was built (4 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: VT | Statement: [Province of Viterbo, vehicleRegistrationCode, VT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: VT Context triple: [Province of Viterbo, vehicleRegistrationCode, VT]
-
A.
VT
VT is the standard two-letter postal abbreviation used to represent the U.S. state of Vermont.
-
B.
VG
VG is the two-letter ISO 3166 country code assigned to the British Virgin Islands.
-
C.
VE
VE is the two-letter ISO 3166-1 alpha-2 country code assigned to Venezuela for international standardization and identification purposes.
-
D.
V
V is the stock ticker symbol for Visa Inc., a leading global payments technology company.
-
E.
VEN
VEN is the three-letter ISO 3166-1 alpha-3 country code assigned to Venezuela for international identification and data standards.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: VT Triple: [Province of Viterbo, vehicleRegistrationCode, VT]
Generated description
VT is the vehicle registration code used on license plates for vehicles registered in the Province of Viterbo in Italy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: VT Target entity description: VT is the vehicle registration code used on license plates for vehicles registered in the Province of Viterbo in Italy.
-
A.
VT
VT is the standard two-letter postal abbreviation used to represent the U.S. state of Vermont.
-
B.
VG
VG is the two-letter ISO 3166 country code assigned to the British Virgin Islands.
-
C.
VE
VE is the two-letter ISO 3166-1 alpha-2 country code assigned to Venezuela for international standardization and identification purposes.
-
D.
V
V is the stock ticker symbol for Visa Inc., a leading global payments technology company.
-
E.
VEN
VEN is the three-letter ISO 3166-1 alpha-3 country code assigned to Venezuela for international identification and data standards.
- F. None of above. chosen
Provenance (5 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_69ad858f74408190bcbd07f967cd7bd0 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adafa673a481909b5024b4e0e1c2a7 |
completed | March 8, 2026, 5:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b28ed941cc81909c35853e793d6ce5 |
completed | March 12, 2026, 10 a.m. |
| NEDg | Description generation | batch_69b2900805d08190afbda5ee5e984b71 |
completed | March 12, 2026, 10:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b2ac4c52d48190a87b1e535c2e8a37 |
completed | March 12, 2026, 12:06 p.m. |
Created at: March 8, 2026, 3:09 p.m.