Triple
T18193028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dübendorf |
E435587
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object | Glatt |
—
|
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: Glatt | Statement: [Dübendorf, hasRiver, Glatt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Glatt Context triple: [Dübendorf, hasRiver, Glatt]
-
A.
Glatt
chosen
Glatt is a river in the Canton of Zürich in Switzerland, known for flowing out of Lake Greifen and joining the Rhine near Glattfelden.
-
B.
Glatter
Glatter is the surname of American television and film director Lesli Linka Glatter, known for her work on acclaimed series such as "Homeland" and "Mad Men."
-
C.
Metzling
Metzling is a small locality that forms part of the municipality of Persenbeug-Gottsdorf in Lower Austria.
-
D.
Shnitzel
Shnitzel is a gruff, rock-skinned chef and dishwasher in the animated series "Chowder," known for his limited vocabulary and deadpan demeanor.
-
E.
Strudel
Strudel is a traditional Central European pastry made from thinly rolled dough filled with sweet or savory ingredients, most famously apple.
- 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_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e0d12b688190842375dcc5d5537c |
completed | April 19, 2026, 2:04 p.m. |
Created at: April 10, 2026, 10:31 a.m.