Triple
T11831366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Komárno |
E281398
|
entity |
| Predicate | hasHarborOn |
P3007
|
FINISHED |
| Object | Váh |
E104365
|
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: Váh | Statement: [Komárno, hasHarborOn, Váh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Váh Context triple: [Komárno, hasHarborOn, Váh]
-
A.
Váh
chosen
Váh is the longest river in Slovakia, flowing through much of the country before joining the Danube.
-
B.
Viotá
Viotá is a rural municipality in the Cundinamarca department of Colombia, known for its coffee production and location in the Andean region southwest of Bogotá.
-
C.
Vajna
Vajna is the surname of Andrew G. Vajna, a prominent Hungarian-American film producer known for co-founding Carolco Pictures and producing major action films such as the Rambo series.
-
D.
Vézina
Vézina is a French-Canadian surname most famously associated with Georges Vézina, the legendary early 20th-century ice hockey goaltender and namesake of the NHL’s Vezina Trophy.
-
E.
White Váh
White Váh is one of the two main headwater streams that join to form the Váh River in northern Slovakia.
- 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_69f2812007dc81908e56fd47b2a94836 |
completed | April 29, 2026, 10:07 p.m. |
Created at: April 8, 2026, 9:43 p.m.