Triple
T19799133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prokuplje |
E475622
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | PK |
—
|
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: PK | Statement: [Prokuplje, vehicleRegistrationCode, PK]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PK Context triple: [Prokuplje, vehicleRegistrationCode, PK]
-
A.
PK
PK is a compact bitmap font file format traditionally used by TeX systems to store rasterized glyphs generated from METAFONT sources.
-
B.
PK
chosen
PK is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Pakistan in international standards and systems.
-
C.
PK
PK is a music producer best known for his work on DMX's influential debut album "It's Dark and Hell Is Hot."
-
D.
PK
PK is a 2014 Indian satirical science fiction comedy film directed by Rajkumar Hirani, known for its critique of religious dogma and superstition through the story of an alien played by Aamir Khan.
-
E.
KP
KP is a subsystem of axiomatic set theory that omits the power set axiom and focuses on sets that are constructible via definable operations.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51b014081908b263e167370529a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e653c930a08190a2263db7170edd71 |
completed | April 20, 2026, 4:26 p.m. |
Created at: April 10, 2026, 1:49 p.m.