Triple
T5239994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deutsch-Wagram |
E118315
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Marchfeld |
E269785
|
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: Marchfeld | Statement: [Deutsch-Wagram, locatedIn, Marchfeld]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marchfeld Context triple: [Deutsch-Wagram, locatedIn, Marchfeld]
-
A.
Marchfeld
chosen
Marchfeld is a fertile lowland region in eastern Austria known for its intensive agriculture and vegetable production.
-
B.
Kiliansdorf
Kiliansdorf is a village and district of the town of Roth in the Bavarian region of Germany.
-
C.
Olbernhau
Olbernhau is a town in Germany’s Ore Mountains renowned for its traditional woodcraft industry, especially the production of Schwibbogen candle arches and other Christmas decorations.
-
D.
Kaltenbach
Kaltenbach is a small Austrian village and ski resort town in the Zillertal Valley, known for its access to the Hochzillertal-Hochfügen ski area.
-
E.
Geisenfeld
Geisenfeld is a small town in Bavaria, Germany, known as the birthplace of prominent early Nazi politician Gregor Strasser.
- 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_69bd4467db0881909b3b0982df32cc8f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b2a52fc8190a22631e1853c74a3 |
completed | March 20, 2026, 4:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf3a8956d88190a6aa9dbab3de54e6 |
completed | March 22, 2026, 12:40 a.m. |
Created at: March 20, 2026, 1:49 p.m.