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updating with new human labels

This commit is contained in:
Matthew Gaughan 2025-10-21 15:19:13 -07:00
parent b198781aa0
commit 90311ca136
5 changed files with 63041 additions and 32 deletions

1949
102125_human_info_sample.csv Normal file

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library(tidyverse)
library(stringr)
library(tidyr)
library(dplyr)
library(purrr)
pre_unified_csv <-"~/analysis_data/100625_unified_w_affil.csv"
pre_unified_df <- read.csv(pre_unified_csv, header = TRUE)
unified_task_df <- pre_unified_df |> filter(comment_type=="task_description")
unified_comment_df <- pre_unified_df |> filter(comment_type!="task_description")
library(scales)
unified_task_df |>
count(source, phase, isAuthorWMF) |>
mutate(pct = round(n / sum(n), 3))
median_n <- unified_comment_df |>
count(AuthorPHID) |>
pull(n) |>
median(na.rm = TRUE)
median_n
median_comments <- pre_unified_df |>
count(TaskPHID) |>
pull(n) |>
median(na.rm=TRUE)
median_comments
human_csv <-"~/analysis_data/102025_human_labels.csv"
human_df <- read.csv(human_csv, header = TRUE)
cleaned_human_df <- human_df |>
mutate(human_label = replace_na(human_label, "NA"),
human_label = str_squish(human_label)) |>
group_by(id, TaskPHID, AuthorPHID, comment_text, task_title, comment_type, priority, source, phase) |>
summarise(human_labels = list(human_label), .groups = "drop")
cleaned_human_df <- cleaned_human_df |>
left_join(pre_unified_df, by = c("id", "TaskPHID", "AuthorPHID"))
median_comments <- human_comment_df |>
count(AuthorPHID) |>
pull(n) |>
median(na.rm=TRUE)
median_comments

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@ -1,27 +1,49 @@
library(tidyverse)
main_csv <-"~/analysis_data/100325_unified_phab.csv"
main_csv <-"~/analysis_data/100625_unified_w_affil.csv"
main_df <- read.csv(main_csv, header = TRUE)
human_csv <-"~/analysis_data/102025_human_labels.csv"
human_df <- read.csv(human_csv, header = TRUE)
selected_task_phids <- unique(human_df$TaskPHID)
set.seed(1893) # For reproducibility
sampled_df <- main_df %>%
group_by(source) %>%
mutate(sampled_TaskPHID = TaskPHID %in% sample(unique(TaskPHID), 40)) %>%
ungroup() %>%
# moment 1 of sampling
#sampled_df <- main_df %>%
# group_by(source) %>%
# mutate(sampled_TaskPHID = TaskPHID %in% sample(unique(TaskPHID), 40)) %>%
# ungroup() %>%
# filter(sampled_TaskPHID) %>%
# select(-sampled_TaskPHID)
# moment 2 of sampling
sampled_tasks <- main_df |>
filter(!(TaskPHID %in% selected_task_phids),
source=="c1",
phase=="3",
isAuthorWMF=="TRUE",
comment_type=="task_description")|>
mutate(sampled_TaskPHID = TaskPHID %in% sample(unique(TaskPHID), 10)) %>%
filter(sampled_TaskPHID) %>%
select(-sampled_TaskPHID)
labeling_sampled_df <- sampled_df %>%
group_by(source) %>%
mutate(
verification_sample = if_else(
TaskPHID %in% sample(unique(TaskPHID), min(8, length(unique(TaskPHID)))), 1L, 0L
)
) %>%
ungroup()
sampled_task_phids <- unique(sampled_tasks$TaskPHID)
sampled_df <- main_df |>
filter(TaskPHID %in% sampled_task_phids)
#labeling_sampled_df <- sampled_df %>%
# group_by(source) %>%
# mutate(
# verification_sample = if_else(
# TaskPHID %in% sample(unique(TaskPHID), min(8, length(unique(TaskPHID)))), 1L, 0L
# )
# ) %>%
# ungroup()
sentence_level_sample <- labeling_sampled_df |>
#sentence_level_sample <- labeling_sampled_df |>
sentence_level_sample <- sampled_df |>
mutate(
cleaned_sentences = lapply(
olmo_cleaned_sentences,
@ -43,4 +65,4 @@ table(sentence_level_sample$verification_sample)
(nrow(sentence_level_sample) / 293) * 1.5
length(unique(sentence_level_sample$TaskPHID))
write.csv(sentence_level_sample, "100625_human_info_sample.csv", row.names = FALSE)
write.csv(sentence_level_sample, "102125_human_info_sample.csv", row.names = FALSE)

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1. SSH tunnel from your workstation using the following command:
ssh -N -L 8787:n3439:57743 mjilg@klone.hyak.uw.edu
and point your web browser to http://localhost:8787
2. log in to RStudio Server using the following credentials:
user: mjilg
password: anx8V7R1X2rfcwUV20H/
When done using RStudio Server, terminate the job by:
1. Exit the RStudio Session ("power" button in the top right corner of the RStudio window)
2. Issue the following command on the login node:
scancel -f 30181212