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👩🏻(prompt): Could you evaluate the result generated by computational method A based on these three aspects: Main entities, main events, event linkage. Result would be provided as screen shot. Please provide precision and recall for the three criteria.
model output
GPT4o Evaluation
🤖(answer): To evaluate the results of the two figures provided, one focusing on individual keyword ranking and the other using network-based community detection to extract top communities, let's break down the evaluation into the following steps:
1. Definitions for Precision and Recall:
Precision: The proportion of relevant instances among the retrieved instances. Here, it measures how many of the identified main entities, events, and linkages are actually correct and relevant.
Recall: The proportion of relevant instances that have been retrieved over the total amount of relevant instances. Here, it measures how many of the actual main entities, events, and linkages the model successfully identified.
2. Evaluation Details
Main Entities
FreePalestine:
Entities like "Hamas," "Palestinian," "military," and "Israel" are captured, focusing on the core participants in the conflict.
Non-relevant terms like "themselves" and abstract entities may dilute the focus.
Zionism:
Entities such as "Islam," "Muslims," "Israel," "Jews," and "territory" are identified, representing key players in the conflict from a Zionist perspective.
There are some irrelevant terms, but they are less frequent compared to relevant entities.
Narrative Network (Top Communities):
FreePalestine:
The narrative network captures entities like "Hamas," "Palestinian," and "soldiers," maintaining focus on critical entities in the conflict.
There’s a mix of both highly relevant and slightly less relevant entities.
Zionism:
The narrative network effectively identifies entities such as "Muslims," "Jews," "territory," and "Israel," which are crucial for the Zionism narrative.
The community detection seems more focused, though some abstract terms could be considered less informative.
Conclusion on Main Entities:
Precision:
Top Narrative Triplets: High, as the method captures relevant entities but includes some irrelevant terms.
Narrative Network: High, with more focused identification of critical entities.
Recall:
Top Narrative Triplets: Moderate, as it captures many main entities but misses others.
Narrative Network: High, as it captures a broad range of relevant entities.
Main Events
Top Narrative Triplets:
FreePalestine:
Events related to military action ("soldiers," "civilian buildings") and political actions are present but abstracted.
Less focus on specific events and more on generalized actions or consequences.
Zionism:
References to actions like "PROTECT," "POSSESS," and "BEHAVE" are made, but again, these are more abstracted rather than specific events.
The triplets suggest certain activities, but not particular incidents.
Narrative Network (Top Communities):
FreePalestine:
The network identifies themes like "supporting Hamas," "dividing a city," and "genocide," which can be linked to events but are more abstract.
Specific events might be less emphasized due to the generalized nature of the network terms.
Zionism:
The network mentions actions like "support," "protect," and "possess," but again, these are more about thematic actions than specific events.
Conclusion on Main Events:
Precision:
Top Narrative Triplets: Moderate, as it focuses on actions and outcomes but not specific events.
Narrative Network: Moderate, capturing relevant themes but abstracting away from specific events.
Recall:
Top Narrative Triplets: Low to Moderate, as fewer specific events are captured.
Narrative Network: Moderate, as it captures broad themes but might miss specific incidents.
Event Linkage
Top Narrative Triplets:
FreePalestine:
Linkages like "REQUIRE_NEED_WANT_HOPE," "RESULT_CONSEQUENCE," and "FACE_CHALLENGE" show how events and actions are conceptually connected.
The linkages are strong but abstracted, lacking direct causal or temporal relationships between specific events.
Zionism:
Connections like "CHANGE_SWITCH," "PROTECT," and "POSSESS" indicate relationships between actions but are similarly abstract.
The focus is on how actions influence each other conceptually.
Narrative Network (Top Communities):
FreePalestine:
The network captures the idea of collective action ("supporting Hamas," "divide a city") and connects these to broader outcomes ("genocide reforms").
However, these linkages are broad and thematic, not specific to temporal event sequences.
Zionism:
Connections like "PROTECT ourselves," "POSSESS to other people" indicate themes of defense and territorial claims.
The linkages focus on broad strategic narratives but again abstract away from specific, sequential events.
Conclusion on Event Linkage:
Precision:
Top Narrative Triplets: High, focusing on how actions and outcomes are conceptually linked but with less emphasis on specific, temporally linked events.
Narrative Network: Moderate, as it abstracts relationships into broader thematic linkages.
Recall:
Top Narrative Triplets: Moderate, as the method captures a good range of linkages but not specific, detailed event sequences.
Narrative Network: Moderate, focusing on thematic connections but less on direct event sequences.
3. Quantitative Precision and Recall Estimation:
Given the qualitative assessments, here are the estimated values:
These values reflect the effectiveness of each method in identifying, linking, and narrating the events and entities within the Israel-Hamas conflict as discussed in the provided results. The narrative network generally performs better in maintaining a thematic and focused narrative, while the top narrative triplets are strong in linking abstract concepts but might miss some details.