Triple
T35743084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BR-43 |
E1033093
|
entity |
| Predicate | partOfRegistrationSeries |
P202611
|
FINISHED |
| Object | Bihar vehicle registration codes |
—
|
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: Bihar vehicle registration codes | Statement: [BR-43, partOfRegistrationSeries, Bihar vehicle registration codes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfRegistrationSeries Context triple: [BR-43, partOfRegistrationSeries, Bihar vehicle registration codes]
-
A.
vehicleNumberInSeries
Indicates the position or sequence number that a specific vehicle holds within a defined series of vehicles.
-
B.
designationSeries
Indicates that one designation belongs to or is part of a broader series of related designations.
-
C.
partOfNicknameSeriesFor
Indicates that one nickname belongs to a series or set of related nicknames associated with the same entity.
-
D.
partOfSeriesType
Indicates that something belongs to a series and specifies the type or category of that series.
-
E.
inscriptionNumber
Indicates the identifying number assigned to a specific inscription within a collection or system.
- F. None of above. chosen
Provenance (4 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_69f76e119d508190a3873cb302063832 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a00a094c44c81908e4501151688a635 |
completed | May 10, 2026, 3:13 p.m. |
| PD | Predicate disambiguation | batch_6a009fcdfd848190841deaad9667d347 |
completed | May 10, 2026, 3:10 p.m. |
| PDg | Predicate description generation | batch_6a00a09383548190b05620e6b185bf05 |
completed | May 10, 2026, 3:13 p.m. |
Created at: May 3, 2026, 4:06 p.m.