Triple
T10401167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maros River |
E245148
|
entity |
| Predicate | hasTributary |
P415
|
FINISHED |
| Object | Körös River |
E237331
|
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: Körös River | Statement: [Maros River, hasTributary, Körös River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Körös River Context triple: [Maros River, hasTributary, Körös River]
-
A.
Körös
chosen
Körös is a river in Central Europe that flows through eastern Hungary and parts of Romania before joining the Tisza River.
-
B.
Eger River
The Eger River is a watercourse in Central Europe that flows through parts of Germany and the Czech Republic, serving as a tributary of the Elbe River.
-
C.
Zala River
The Zala River is a major river in western Hungary that drains a large catchment area before emptying into Lake Balaton.
-
D.
Crna River
The Crna River is a significant river in North Macedonia that flows through the Pelagonia region before joining the Axios (Vardar) River.
-
E.
Vouga River
The Vouga River is a river in central Portugal that flows through the Viseu District before emptying into the Atlantic Ocean near Aveiro.
- 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9e2f11c8190b30695cba2975544 |
completed | April 7, 2026, 11:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3a8c95ca081908ceaa89eef87fbc9 |
completed | April 18, 2026, 3:52 p.m. |
Created at: April 6, 2026, 12:07 p.m.