Triple
T20466479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seeham |
E502061
|
entity |
| Predicate | hasNearbyLake |
P17985
|
FINISHED |
| Object | Grabensee |
—
|
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: Grabensee | Statement: [Seeham, hasNearbyLake, Grabensee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grabensee Context triple: [Seeham, hasNearbyLake, Grabensee]
-
A.
Grabensee
chosen
Grabensee is a small lake in the Austrian state of Salzburg, known for its natural surroundings and recreational opportunities.
-
B.
Hallwilersee
Hallwilersee is a scenic lake in the Swiss cantons of Aargau and Lucerne, popular for recreation, boating, and nature conservation.
-
C.
Alpnachersee
Alpnachersee is a small alpine lake in central Switzerland that forms a narrow southwestern arm of Lake Lucerne near the town of Alpnach.
-
D.
Rifflsee
Rifflsee is a scenic alpine lake in the Austrian Tyrol, known for its turquoise waters and mountain surroundings.
-
E.
Gelmersee
Gelmersee is a high-altitude reservoir and scenic mountain lake in the Bernese Oberland region of Switzerland, popular for hiking and its steep funicular access.
- 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_69e0b4ae5f1081908768b0c9a3a0bf38 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e696aa0794819082c9989b1f7e9f37 |
completed | April 20, 2026, 9:12 p.m. |
Created at: April 16, 2026, 11:33 a.m.