Figure 3 shows the distribution of the input document size (both axes are on a log scale). Most

![0_image_0.png](0_image_0.png) documents have an XML size between 1KB and 100KB. The size of the biggest document is about 5.7 MB. We used 20 machines to annotate these documents. Most of these machines were standard Personal Computers with 1GB of RAM and 2.9 or 3.1 GHz processor. We also used a computer with 8GB of RAM and two 2.8GHz Xeon (dual-core) processors. Their operating system were either Debian Linux or Mandrake Linux. The server and three NLP clients were running on the 8GB/biprocessor. Only one NLP client was running on each standard Personal Computer. Even if a real benchmark requires several tests to evaluate the performance, we consider this performance as an interesting indication of the platform processing time. Timers are run between each function call in order to measure how long each step is (user-time-wise). We used the functions provided in the Time::Hires Perl package. All the time results are recorded in the annotated XML documents.

| Average number of units       | Total number of units in the   |             |
|-------------------------------|--------------------------------|-------------|
| by document                   | document collection            |             |
| Tokens                        | 5,021.9                        | 277,846,470 |
| Named entities                | 81.88                          | 4,530,368   |
| Words                         | 1,912.65                       | 105,821,243 |
| Sentences                     | 85.41                          | 4,726,003   |
| Part-of-speech tags and lemma | 1883.5                         | 104,208,536 |
| Terms                         | 250.76                         | 13,874,089  |

Table 3: Average and total numbers of linguistic units.

The annotation of the documents was completed in 35 hours. Table 3 shows the total number of entities found in the document collection. 106 million words and 4.72 million sentences