Triple
T16956226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | György |
E411309
|
entity |
| Predicate | shortForm |
P43
|
FINISHED |
| Object | Gyurka |
E1242447
|
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: Gyurka | Statement: [György, shortForm, Gyurka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gyurka Context triple: [György, shortForm, Gyurka]
-
A.
Gyuri
chosen
Gyuri is a Hungarian given name, commonly used as a diminutive or familiar form of the name György.
-
B.
Gyergyay
Gyergyay is a Hungarian-origin surname associated with the actor Steven Geray (born István Gyergyay).
-
C.
Gyál
Gyál is a town in central Hungary that functions as a suburban residential area near Budapest within Pest County.
-
D.
Gárdony
Gárdony is a Hungarian town and popular resort area on the southern shore of Lake Velence, known for its beaches, thermal waters, and recreational tourism.
-
E.
Dobogó
Dobogó is a neighborhood within Budapest’s 11th District, known primarily as an emerging urban area undergoing development on the city’s Buda side.
- 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_69d886c9c9d481909afe222093641cae |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d01c7b408190b5a2b6c62b050b76 |
completed | April 18, 2026, 6:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00dc06e6b481908d8032f5772762c9 |
completed | May 10, 2026, 7:27 p.m. |
Created at: April 10, 2026, 5:31 a.m.