Triple
T12311859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Clausen |
E293497
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Clausen |
E349449
|
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: Clausen | Statement: [George Clausen, familyName, Clausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clausen Context triple: [George Clausen, familyName, Clausen]
-
A.
Clausen
chosen
Clausen is a historic quarter of Luxembourg City known for its nightlife, old breweries, and picturesque setting along the Alzette River.
-
B.
Clausena
Clausena is a genus of flowering plants in the citrus family known for its aromatic shrubs and trees, some of which are used in traditional medicine and as spices.
-
C.
Krause
Krause is a German-origin surname borne by numerous notable individuals across sports, politics, science, and the arts.
-
D.
Cressner
Cressner is the sadistic, wealthy gambler and primary villain in Stephen King’s short story “The Ledge,” known for forcing a man to risk his life by walking around a narrow ledge high above the city.
-
E.
Bischoffen
Bischoffen is a small municipality in the central German state of Hesse, situated in a rural area characterized by forests, hills, and nearby reservoirs.
- 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_69d6ab6a2b50819082f6aedd32ed608a |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f02c0508190b10c0627cdaaba76 |
completed | April 10, 2026, 6:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e84fa708190854afc6afd425fd7 |
completed | May 2, 2026, 3:55 p.m. |
Created at: April 8, 2026, 9:53 p.m.