Triple
T5234254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bitterfeld-Wolfen |
E118183
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Witten |
E317101
|
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: Witten | Statement: [Bitterfeld-Wolfen, hasTwinTown, Witten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Witten Context triple: [Bitterfeld-Wolfen, hasTwinTown, Witten]
-
A.
Witten
Witten is a surname most notably associated with Edward Witten, a leading theoretical physicist and key figure in string theory and mathematical physics.
-
B.
Witten
chosen
Witten is a city in the Ruhr region of western Germany known for its industrial heritage and location along the Ruhr River.
-
C.
Schreiber
Schreiber is a surname most notably associated with Stuart L. Schreiber, a prominent American chemist known for his pioneering work in chemical biology and drug discovery.
-
D.
Wess
Wess is a given name, typically used as a shortened or variant form of Wesley.
-
E.
Wirtinger
Wirtinger is a surname most notably associated with Austrian mathematician Wilhelm Wirtinger, known for his contributions to complex analysis and knot theory.
- 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_69bd7b04c03481908d901788ce2c4128 |
completed | March 20, 2026, 4:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bef818f31c8190a26950dcd9d6a895 |
completed | March 21, 2026, 7:57 p.m. |
Created at: March 20, 2026, 1:49 p.m.