Triple
T11831364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Komárno |
E281398
|
entity |
| Predicate | hasBridgeTo |
P36619
|
FINISHED |
| Object | Komárom |
E954175
|
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: Komárom | Statement: [Komárno, hasBridgeTo, Komárom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Komárom Context triple: [Komárno, hasBridgeTo, Komárom]
-
A.
Komárom
chosen
Komárom is a Hungarian town on the Danube River known for its historic fortifications and its twin-city relationship with Komárno in Slovakia.
-
B.
Kalocsa
Kalocsa is a historic town in southern Hungary known as an important Roman Catholic archiepiscopal center and for its traditional paprika production and folk art.
-
C.
Komárno
Komárno is a historic town and river port in southern Slovakia, situated at the confluence of the Danube and Váh rivers on the border with Hungary.
-
D.
Dunakeszi
Dunakeszi is a town in Hungary located just north of Budapest, known as a rapidly growing suburban and commuter settlement along the Danube in Pest County.
-
E.
Belá
Belá is a mountain river in northern Slovakia known for its clear waters, dynamic flow, and popularity among whitewater enthusiasts.
- 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_69d6ab276f8c8190b1966a0ef11349ac |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a62c95988190a45dbaa7001c8846 |
completed | April 10, 2026, 7:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f48a35f9d081909c4cc7d7ce78e4fc |
completed | May 1, 2026, 11:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.