Triple
T7277050
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crișana |
E163056
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Hungary |
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: Hungary | Statement: [Crișana, borders, Hungary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hungary Context triple: [Crișana, borders, Hungary]
-
A.
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.
-
B.
Austria and Hungary
Austria and Hungary are neighboring Central European countries with closely linked histories, cultures, and transportation networks.
-
C.
Ungar
Ungar is a surname of Germanic and Central European origin, historically associated with people from Hungary or of Hungarian descent.
-
D.
Slovakia and Hungary
Slovakia and Hungary are neighboring Central European countries that share a significant stretch of their border along the Danube River.
-
E.
Austria
Austria is a landlocked Central European country known for its Alpine landscapes, rich cultural and musical heritage, and status as a prosperous, democratic member of the European Union.
- 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_69c6885c5964819085b209701769877f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb2f239c819097c1ac4d6de8b0e5 |
completed | March 27, 2026, 8:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7e532a7f08190a5c0b1167dc0be44 |
completed | March 28, 2026, 2:26 p.m. |
Created at: March 27, 2026, 2:59 p.m.