Triple
T14572342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aiviekste River |
E341948
|
entity |
| Predicate | source |
P409
|
FINISHED |
| Object | Lake Lubāns |
E1106449
|
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: Lake Lubāns | Statement: [Aiviekste River, source, Lake Lubāns]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lake Lubāns Context triple: [Aiviekste River, source, Lake Lubāns]
-
A.
Lake Lubāns
chosen
Lake Lubāns is the largest lake in Latvia, known for its extensive wetlands and importance as a habitat for migratory birds.
-
B.
al-Qusayr Lake
al-Qusayr Lake is a body of water located within Syria’s Aleppo Governorate, known as a local inland lake in the country’s north.
-
C.
Lake Assad
Lake Assad is Syria’s largest artificial lake, created on the Euphrates River to provide water storage, irrigation, and hydroelectric power.
-
D.
Lake Qaraoun
Lake Qaraoun is Lebanon’s largest artificial lake, created by damming the Litani River and serving as a key source of irrigation, hydropower, and water storage in the Beqaa Valley.
-
E.
Bou Areg Lagoon
Bou Areg Lagoon is a coastal lagoon in northeastern Morocco known for its rich biodiversity and importance as a habitat for migratory birds.
- 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_69d822dcc6248190bed689984bceb0e2 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb3f33b1c8190bb447788bfd28d51 |
completed | April 14, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd94b5d97481908b2d3d531817a3a6 |
completed | May 8, 2026, 7:45 a.m. |
Created at: April 10, 2026, 1:24 a.m.