Triple
T14632117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Humberside |
E343502
|
entity |
| Predicate | hadRegistrationPlateCode |
P62402
|
FINISHED |
| Object | H |
—
|
LITERAL 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: H | Statement: [Humberside, hadRegistrationPlateCode, H]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadRegistrationPlateCode Context triple: [Humberside, hadRegistrationPlateCode, H]
-
A.
hasPlate
Indicates that one entity possesses, is equipped with, or includes a plate as part of its attributes or components.
-
B.
hasHistoricRegistrationPlateCode
Indicates that an entity is associated with a specific code assigned to its historic (vintage/classic) vehicle registration plate.
-
C.
vehicleRegistrationCode
Indicates the official registration identifier assigned to a vehicle, typically used for legal identification and record-keeping.
-
D.
usesCodeOnPlates
chosen
Indicates that an entity applies or employs a specific code or coding system on plates.
-
E.
hasCarNumberPreviously
Indicates that an entity has been associated with a specific car number at some earlier time before the current context.
- 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_69d822dffc3c8190aa173b90761bffda |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4a912248190a3df7f821395c776 |
completed | April 14, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69de657359c88190b082e3e9f86fc1d7 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:26 a.m.