Triple
T20672810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M4 motorway (Hungary) |
E508072
|
entity |
| Predicate | passesNear |
P416
|
FINISHED |
| Object | Vecsés |
—
|
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: Vecsés | Statement: [M4 motorway (Hungary), passesNear, Vecsés]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vecsés Context triple: [M4 motorway (Hungary), passesNear, Vecsés]
-
A.
Vecsés
chosen
Vecsés is a town in central Hungary, located near Budapest and known for its proximity to Budapest Ferenc Liszt International Airport.
-
B.
Vilmos
Vilmos is a masculine given name of Hungarian origin, equivalent to William in English.
-
C.
Zebegény
Zebegény is a picturesque riverside village in northern Hungary, known for its scenic setting in the Danube Bend and its popularity as a hiking and holiday destination.
-
D.
Sarolt
Sarolt was a prominent 10th-century Hungarian noblewoman and duchess, influential in the Christianization and early state formation of Hungary as the wife of Grand Prince Géza and mother of King Stephen I.
-
E.
Teleki
Teleki is a Hungarian noble family name most notably associated with Pál Teleki, a geographer and two-time prime minister of Hungary in the early 20th century.
- 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_69e0b4c1164881909a3bf1e3ddb2bc32 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b5cb1fc88190805f623e93a70368 |
completed | April 20, 2026, 11:24 p.m. |
Created at: April 16, 2026, 11:44 a.m.