Triple
T25216134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noicattaro |
E631831
|
entity |
| Predicate | hasProvinceVehicleCode |
P99880
|
FINISHED |
| Object | BA |
—
|
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: BA | Statement: [Noicattaro, hasProvinceVehicleCode, BA]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProvinceVehicleCode Context triple: [Noicattaro, hasProvinceVehicleCode, BA]
-
A.
hasProvincialCode
chosen
Indicates that an entity is associated with a specific provincial code that identifies its province or administrative region.
-
B.
hasProvinceType
Indicates that an entity is associated with a province classified by a specific type or category.
-
C.
hasProvinceOrRegion
Indicates that one entity includes, is associated with, or is located within a specific province or region as an administrative or geographic subdivision.
-
D.
hasProvinceName
Indicates that an entity (such as a province or region) bears or is associated with a specific province name.
-
E.
hasCountyNumberPlateCode
Indicates that an entity (such as a vehicle or registration) bears a number plate code that corresponds to a specific county.
- F. None of above.
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_69e75a8d1aa48190a4320acd3654762c |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f69edbb7648190bd89c57e0932eac1 |
completed | May 3, 2026, 1:03 a.m. |
| PD | Predicate disambiguation | batch_69f69d17e8d48190b30bcc2f4bd81eb2 |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 21, 2026, 12:59 p.m.