Triple
T19807341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Syas River |
E475847
|
entity |
| Predicate | hasRightTributary |
P415
|
FINISHED |
| Object | Pasha River |
—
|
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: Pasha River | Statement: [Syas River, hasRightTributary, Pasha River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pasha River Context triple: [Syas River, hasRightTributary, Pasha River]
-
A.
Pasha River
chosen
The Pasha River is a waterway in northwestern Russia that flows through the Leningrad Oblast before joining the Svir River.
-
B.
Zay River
The Zay River is a waterway in Russia’s Republic of Tatarstan that serves as a significant local river for towns such as Almetyevsk.
-
C.
Sana River
The Sana River is a significant river in northwestern Bosnia and Herzegovina that flows through towns such as Prijedor before joining the Una River.
-
D.
Bani River
The Bani River is a significant West African waterway that joins the Niger River in Mali, contributing substantially to its flow and regional agriculture.
-
E.
Al Raha River
Al Raha River is a lazy river-style water ride at Yas Waterworld in Abu Dhabi, offering a relaxing float through themed surroundings.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65428f5c48190be6ae0d6a77675d2 |
completed | April 20, 2026, 4:28 p.m. |
Created at: April 10, 2026, 1:49 p.m.