Triple
T15946789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alz |
E386705
|
entity |
| Predicate | sourceLocation |
P40
|
FINISHED |
| Object | Chiemsee |
E41133
|
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: Chiemsee | Statement: [Alz, sourceLocation, Chiemsee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chiemsee Context triple: [Alz, sourceLocation, Chiemsee]
-
A.
Chiemsee
chosen
Chiemsee is one of Germany’s largest lakes, famed for its scenic Alpine setting and historic islands such as Herrenchiemsee with its royal palace.
-
B.
Altmühlsee
Altmühlsee is an artificial recreational lake in Bavaria, Germany, popular for swimming, sailing, and nature conservation.
-
C.
Wörthsee
Wörthsee is a scenic lake and popular recreational destination in Upper Bavaria, Germany, known for its clear waters and proximity to Munich.
-
D.
Tegernsee
Tegernsee is a picturesque alpine lake in southern Germany renowned for its clear waters, surrounding mountains, and popular spa and resort towns.
-
E.
Königssee
Königssee is a picturesque alpine lake in southeastern Germany, renowned for its emerald-green waters, steep surrounding mountains, and status as one of the cleanest lakes in the country.
- 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156d1a4c08190afc325491ba38870 |
completed | April 16, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffcf14ab088190b1d2f1f6b18bf85d |
completed | May 10, 2026, 12:19 a.m. |
Created at: April 10, 2026, 4:53 a.m.