Triple
T11734449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Ávila |
E278988
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | AV |
E794751
|
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: AV | Statement: [Province of Ávila, vehicleRegistrationCode, AV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AV Context triple: [Province of Ávila, vehicleRegistrationCode, AV]
-
A.
AV
chosen
AV is the Italian vehicle registration code assigned to the province of Avellino in the Campania region.
-
B.
AV
AV is the two-letter IATA airline designator assigned to Avianca, the flag carrier of Colombia and one of Latin America’s largest airlines.
-
C.
Av
Av is the fifth month of the Hebrew calendar, traditionally associated with both national tragedies and consolation in Jewish history and observance.
-
D.
AV.
AV. is the stock ticker symbol for Aviva plc, a major British multinational insurance, savings, and retirement services company listed on the London Stock Exchange.
-
E.
AVE
AVE is Spain’s high-speed rail service, connecting major cities like Madrid and Barcelona with fast, long-distance trains.
- 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_69d6aaffec6881908bead509e8621742 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4daa7f48190896fc7653e9dd70b |
completed | April 10, 2026, 7:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f0199f595081908c10ecd7dd3900e7 |
completed | April 28, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:41 p.m.