Triple
T12566794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Westphalia |
E295497
|
entity |
| Predicate | containsSettlement |
P847
|
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: [Province of Westphalia, containsSettlement, Witten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Witten Context triple: [Province of Westphalia, containsSettlement, 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.
Schreiber
Schreiber is a small township and community located along the north shore of Lake Superior in northwestern Ontario, Canada.
-
E.
Wess
Wess is a given name, typically used as a shortened or variant form of Wesley.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9549611c081909e611756f3cce7f0 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6558f87b081909ba179b49bae3913 |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 8, 2026, 11:49 p.m.