Triple
T22736883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamburg |
E562294
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object | Alster |
—
|
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: Alster | Statement: [Hamburg, hasRiver, Alster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alster Context triple: [Hamburg, hasRiver, Alster]
-
A.
Alster
chosen
The Alster is a river and series of lakes in Hamburg, Germany, that form a central recreational and scenic landmark of the city.
-
B.
Union Lake
Union Lake is an inland lake in Oakland County, Michigan, known for recreational boating, fishing, and lakeside residential communities.
-
C.
Avon Lake
Avon Lake is a suburban city in northern Ohio situated along the Lake Erie shoreline, known for its residential communities and lakefront parks.
-
D.
Silver Lake
Silver Lake is a scenic recreational lake located within Blackwell Forest Preserve in DuPage County, Illinois.
-
E.
Silver Lake
Silver Lake is a scenic alpine lake in California’s Eastern Sierra Nevada, popular for fishing, boating, and outdoor recreation.
- 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_69e24550859c81908727d91efc3a81b4 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1796fc2a88190a4d86b421345b088 |
completed | April 29, 2026, 3:22 a.m. |
Created at: April 17, 2026, 3:22 p.m.