Triple
T17083144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wittmundhafen Air Base |
E414525
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Wittmund |
—
|
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: Wittmund | Statement: [Wittmundhafen Air Base, locatedIn, Wittmund]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wittmund Context triple: [Wittmundhafen Air Base, locatedIn, Wittmund]
-
A.
Wittmund
chosen
Wittmund is a small town in Lower Saxony, Germany, known as an administrative center in the East Frisia region.
-
B.
Himmerod
Himmerod is a historic Cistercian abbey in the Eifel region of Germany, known as a religious and cultural center since the Middle Ages.
-
C.
Vellmar
Vellmar is a town in the German state of Hesse, located just north of Kassel.
-
D.
Ramstedt
Ramstedt is a Finnish surname most notably borne by linguist and diplomat Gustaf John Ramstedt, known for his pioneering work in Altaic and Mongolic studies.
-
E.
Breckerfeld
Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbe4d3908190b23ce3c2d3fe7d14 |
completed | April 18, 2026, 7:30 p.m. |
Created at: April 10, 2026, 5:35 a.m.