
| Instances   | Classes   | Relations   |      |      |       |             |             |      |             |             |       |      |       |      |
|-------------|-----------|-------------|------|------|-------|-------------|-------------|------|-------------|-------------|-------|------|-------|------|
| Change      | Time      | Prec        | Rec  | F    | Time  | YAGO ⊆ IMDb | IMDb ⊆ YAGO | Time | YAGO ⊆ IMDb | IMDb ⊆ YAGO |       |      |       |      |
| to prev.    | Num       | Prec        | Num  | Prec | Prec  | Rec         | Prec        | Rec  |             |             |       |      |       |      |
| -           | 16h47m    | 84 %        | 75 % | 79 % | -     | -           | -           | -    | -           | 4min        | 91 %  | 73 % | 100 % | 60 % |
| 40.2 %      | 11h44m    | 94 %        | 89 % | 91 % | -     | -           | -           | -    | -           | 5min        | 91 %  | 73 % | 100 % | 80 % |
| 6.6 %       | 11h48m    | 94 %        | 90 % | 92 % | -     | -           | -           | -    | -           | 5min        | 100 % | 80 % | 100 % | 80 % |
| 0.2 %       | 11h44m    | 94 %        | 90 % | 92 % | 2h17m | 8           | 100 %       | 135k | 28 %        | 6min        | 100 % | 80 % | 100 % | 80 % |

Table 5: Results on matching YAGO and IMDb **over iterations 1–4**
consider only the maximally assigned relation, because the **relations do not form**
a hierarchy in YAGO and DBpedia**. In most cases one assignment dominates**
clearly. Table 4 shows some of the alignments. paris finds non-trivial alignments of more fine-grained relations to more coarse-grained **ones, of inverses, of**
symmetric relations, and of relations with completely different names. There are a few plainly wrong alignments, but most errors come from semantic differences that do not show in practice (e.g., *burialPlace* **is semantically different**
from *deathPlace***, so we count it as an error, even though in most cases the two**
will coincide). Recall is hard to estimate, because not all relations have a counterpart in the other ontology and some relations are poorly populated. We only note that we find alignments for half of YAGO**'s relations in** DBpedia.

YAGO vs. IMDb. **Next, we were interested in the performance of** paris on ontologies that do not derive from from the same source. For this purpose, we constructed an RDF ontology from the IMDb. IMDb **is predestined for the**
matching, because it is huge and there is an existing gold standard: YAGO **contains some mappings to** IMDb **movie identifiers, and we could construct such a**
mapping for many persons from Wikipedia infoboxes. The content of the IMDb database is available for download as plain-text files.14 **The format of each file**
is *ad hoc* **but we transformed the content of the database in a fairly straightforward manner into a collection of triples. For instance, the file** actors.list **lists**
for each actor x the list of all movies y that x **was cast in, which we transformed**
into facts *actedIn*(x, y**). Unfortunately, the plain-text database does not contain**
IMDb movie and person identifiers (those that we use for comparing **to the gold**
standard). Consequently, we had to obtain these identifiers **separately. For this**
purpose, and to avoid having to access each Web page of the IMDb **Web site,**
which would require much too many Web server requests, we used the advanced search feature of IMDb15 **to obtain the list of all movies from a given year, or of**
all persons born in a certain year, together with their identifiers and everything needed to connect to the plain-text databases. Since our IMDb **ontology has**
only 24 relations, we manually created a gold standard for relations, aligning 15 of them to YAGO **relations. As Table 5 shows,** paris **took much longer**
for each iteration than in the previous experiment. The results are convincing, with an F-score of 92 % for the instances. This is a considerable improvement over a baseline approach that aligns entities by matching their *rdfs:label* properties (achieving 97 % precision and only 70 % recall, with an **F-score of 82 %).**
Examining by hand the few remaining alignment errors revealed the following patterns:
14http://www.imdb.com/interfaces\#plain 15http://akas.imdb.com/search/