Triple
T10351507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Budapest Nyugati railway station |
E243891
|
entity |
| Predicate | operator |
P179
|
FINISHED |
| Object | MÁV |
E857878
|
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: MÁV | Statement: [Budapest Nyugati railway station, operator, MÁV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MÁV Context triple: [Budapest Nyugati railway station, operator, MÁV]
-
A.
MÁV
chosen
MÁV is the Hungarian State Railways company, responsible for operating most of Hungary’s national rail network and related infrastructure.
-
B.
Austrian Airlines
Austrian Airlines is the flag carrier airline of Austria, operating an extensive network of European and long-haul flights from its main hub in Vienna.
-
C.
Flughafen Wien AG
Flughafen Wien AG is an Austrian publicly listed company that operates and manages Vienna International Airport and related airport services.
-
D.
Malev Hungarian Airlines
Malev Hungarian Airlines was the former national flag carrier of Hungary, operating scheduled passenger flights across Europe and beyond until its closure in 2012.
-
E.
Czech Airlines
Czech Airlines is the national flag carrier of the Czech Republic, operating scheduled passenger flights across Europe and to select long-haul destinations.
- 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_69d381b22b8c8190aaed476be5f872a9 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9489f9481908fc1c818e81c1cc2 |
completed | April 7, 2026, 11:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7951e65948190a25e559ba94be3c7 |
completed | April 9, 2026, 12:01 p.m. |
Created at: April 6, 2026, 11:57 a.m.