Triple
T15381601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dawn Clark Netsch |
E367816
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Netsch |
E1149664
|
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: Netsch | Statement: [Dawn Clark Netsch, familyName, Netsch]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Netsch Context triple: [Dawn Clark Netsch, familyName, Netsch]
-
A.
Netsch
chosen
Netsch is the surname of Walter Andrew Netsch Jr., an influential American architect known for his distinctive modernist designs and work on academic and civic buildings.
-
B.
Stechow-Ferchesar
Stechow-Ferchesar is a small rural municipality in the Havelland district of Brandenburg, Germany.
-
C.
Bramsche
Bramsche is a town in Lower Saxony, Germany, known for its location near Osnabrück and its historical textile industry.
-
D.
Ruwer
Ruwer is a small wine-growing region in Germany’s Mosel area, noted for its cool climate and production of light, crisp white wines.
-
E.
Nischel
Nischel is the local colloquial nickname for the large Karl Marx Monument in Chemnitz, Germany.
- 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e61928c81908852c355d537ed9c |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff0b5bc43c81908ffdb7819e3660d9 |
completed | May 9, 2026, 10:24 a.m. |
Created at: April 10, 2026, 3:19 a.m.