Triple
T19491657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Witzenhausen |
E487665
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Witzenhausen old town |
—
|
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: Witzenhausen old town | Statement: [Witzenhausen, hasPart, Witzenhausen old town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Witzenhausen old town Context triple: [Witzenhausen, hasPart, Witzenhausen old town]
-
A.
Witzenhausen
chosen
Witzenhausen is a small town in northern Hesse, Germany, known for its cherry orchards and agricultural research institutions.
-
B.
Wittmund
Wittmund is a small town in Lower Saxony, Germany, known as an administrative center in the East Frisia region.
-
C.
Walzenhausen
Walzenhausen is a Swiss village and municipality in the canton of Appenzell Ausserrhoden, known for its scenic location above Lake Constance and views over the Rhine Valley.
-
D.
Wittighausen
Wittighausen is a small municipality in the Main-Tauber district of Baden-Württemberg in southern Germany.
-
E.
Willingshausen
Willingshausen is a small municipality in central Germany known for its historic artists’ colony and rural cultural heritage.
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6348e01b88190a513d0e256161fcd |
completed | April 20, 2026, 2:13 p.m. |
Created at: April 10, 2026, 1:39 p.m.