Triple
T244996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hungary |
E5017
|
entity |
| Predicate | ISO3166-1Alpha3 |
P189
|
FINISHED |
| Object | HUN |
E5017
|
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: HUN | Statement: [Hungary, ISO3166-1Alpha3, HUN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HUN Context triple: [Hungary, ISO3166-1Alpha3, HUN]
-
A.
Hazaragi
Hazaragi is a variety of Persian primarily spoken by the Hazara people of central Afghanistan and surrounding regions, distinguished by its unique phonology and significant Turkic and Mongolic influences.
-
B.
HAV
HAV is the IATA airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
-
C.
Kichwa
Kichwa is a Quechuan indigenous language variety widely spoken by Andean communities in Ecuador and neighboring regions.
-
D.
Hungarian Diet
The Hungarian Diet was the historic legislative assembly of the Kingdom of Hungary, composed of the nobility and clergy, which played a central role in approving laws, taxes, and matters of succession.
-
E.
Hungary
chosen
Hungary is a landlocked Central European country known for its rich history, distinct language (Hungarian), and capital city Budapest, famed for its thermal baths and architecture.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d10ac248190a98dedabf5358668 |
completed | Feb. 28, 2026, 3:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a36cf4d8608190bf3d33ee6b93aae0 |
completed | Feb. 28, 2026, 10:32 p.m. |
Created at: Feb. 28, 2026, 2:53 a.m.