Triple
T21281940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Várpalota |
E524547
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object | Várpalota (Hungarian) |
—
|
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: Várpalota (Hungarian) | Statement: [Várpalota, hasNameInLanguage, Várpalota (Hungarian)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Várpalota (Hungarian) Context triple: [Várpalota, hasNameInLanguage, Várpalota (Hungarian)]
-
A.
Várpalota
chosen
Várpalota is a town in western Hungary known for its historical castle and industrial heritage.
-
B.
Vajdahunyad (Hungarian)
Vajdahunyad is the Hungarian name for Hunedoara, a historic city in Transylvania, Romania, best known for its impressive Gothic-Renaissance Corvin Castle.
-
C.
Várnegyed
Várnegyed is Budapest’s historic Castle District, known for its medieval streets, Buda Castle complex, and panoramic views over the Danube and the city.
-
D.
Pilisvörösvár
Pilisvörösvár is a town in central Hungary known for its German minority heritage and proximity to Budapest.
-
E.
Tiszaföldvár
Tiszaföldvár is a small town in eastern Hungary known for its agricultural surroundings and location near the Tisza River.
- 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_69e0b5171f6c8190a5d57201ede73811 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e736d249fc8190b0b310467ddeac3c |
completed | April 21, 2026, 8:35 a.m. |
Created at: April 16, 2026, 4:02 p.m.