Triple
T5098393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kierling |
E114922
|
entity |
| Predicate | locatedInAdministrativeEntity |
P40
|
FINISHED |
| Object | Klosterneuburg |
E187962
|
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: Klosterneuburg | Statement: [Kierling, locatedInAdministrativeEntity, Klosterneuburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Klosterneuburg Context triple: [Kierling, locatedInAdministrativeEntity, Klosterneuburg]
-
A.
Klosterneuburg
chosen
Klosterneuburg is an Austrian town near Vienna, known for its historic Augustinian monastery and wine-growing tradition along the Danube River.
-
B.
Vöcklabruck
Vöcklabruck is a small historic town in Upper Austria known as a regional center near the Attersee lake and the foothills of the Alps.
-
C.
Tulln an der Donau
Tulln an der Donau is an Austrian town on the Danube River, known for its rich history and as the birthplace of painter Egon Schiele.
-
D.
Schärding
Schärding is a historic Austrian town on the border with Germany, known for its well-preserved baroque old town and riverside setting.
-
E.
Gmunden
Gmunden is a picturesque town in Upper Austria known for its lakeside setting on the Traunsee and its historic ceramics industry.
- 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_69bd443fc49c819089629c00e311310c |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7567d21081909227ed8f08b74c71 |
completed | March 20, 2026, 4:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bee067be548190b280674ebf125ca3 |
completed | March 21, 2026, 6:16 p.m. |
Created at: March 20, 2026, 1:40 p.m.