Molecular Facts: Desiderata for Decontextualization in LLM Fact Verification (2024)

Abstract: Automatic factuality verification of large language model (LLM) generations is becoming more and more widely used to combat hallucinations. A major point of tension in the literature is the granularity of this fact-checking: larger chunks of text are hard to fact-check, but more atomic facts like propositions may lack context to interpret correctly. In this work, we assess the role of context in these atomic facts. We argue that fully atomic facts are not the right representation, and define two criteria for molecular facts: decontextuality, or how well they can stand alone, and minimality, or how little extra information is added to achieve decontexuality. We quantify the impact of decontextualization on minimality, then present a baseline methodology for generating molecular facts automatically, aiming to add the right amount of information. We compare against various methods of decontextualization and find that molecular facts balance minimality with fact verification accuracy in ambiguous settings.

## introduction large language models (llms) have emerged as powerful tools for delivering knowledge to users, either via closed-book generation or retrievalaugmented systems. however, these systems may not always produce correct facts @xcite , an instance of the "hallucination" problem @xcite @xcite . recent research has shown the potential of llms to identify unfaithful content and enable automatic fact-checking and attribution against sources @xcite @xcite @xcite @xcite @xcite . a key step in this process is to break down generated content into individual atomic claims (fabbri 1 https://github.com/anisha2102/molecular_facts she won a medal at the european athletics championships ann jansson is a swedish former footballer who scored sweden women's national football team's first ever goal in 1974. in @xcite in december 2017. ann jansson is also a pioneer in international women's walking, breaking several european records and winning a medal at the european athletics championships in 1986. she began her writing @xcite ann jansson (born 1 july 1958) is a swedish former racewalking athlete. she represented @xcite walking cup. she was a medallist at the european athletics championships in 1986. she was a pioneer in @xcite ann jansson, a swedish footballer, won a medal at the european athletics championships. ## desiderata for decontextualization we propose desiderata to determine the optimal level of decontextualization required for atomic facts. an atomic fact is defined as a discrete unit of information, derived from a broader claim, and variously described in the literature as propositions, subclaims, summary content units, or atomic content units @xcite @xcite @xcite . although an atomic fact theoretically represents a singular conceptual unit, recent nlp work using this does not typically give this a rigorous definition from the standpoint of semantics. @xcite demonstrate a high variation in the number of subclaims generated by different decomposition methods, with the macro-average of subclaims per biography ranging from 20.2 using the method by @xcite to 32.9 with the approach by @xcite . note that in figure 1 , she was a medallist at the european athletics championships in 1986 could be kept as one unit or broken into three facts evaluating her status as a medallist, the venue, and the date. ## method: producing molecular facts we use a two-step process to refine an atomic fact into a molecular fact using gpt-4-turbo-2024-04-09 @xcite . our methodology makes the assumption that the ambiguity is typically restricted to a single entity in the claim. this is the case for the datasets we study in this work, described in section 4.5. ## experiment: minimality & localization we begin our analysis of decontextualization with a controlled experiment to illustrate problems with error localization due to loss of minimality discussed in criterion 2 in section 2.1. minimality is more difficult to evaluate than decontextuality. less minimal facts impact error localization and can potentially lead to errors where an ancillary part of the claim leads to the whole claim being judged as wrong @xcite . however, precisely measuring the harms of this is not easy without taking into account the downstream uses of error localization systems such as answer refinement @xcite or fine-tuning @xcite . to measure the effects in a controlled way, we design a method for synthetic evidence generation as summarized in figure 2 . our goal is to illustrate when decontextualized atomic facts actually contain multiple facts in a way that could impact error localization. we then study how many of these cases truly show this problem. to study the impact of information addition, we consider two baselines simple-decontext and safe-decontext which respectively have less and more restrictive prompts for including new information from the context to revise an atomic claim. ## experiment: ambiguous biographies we now analyze to what extent our molecular facts add the correct information to decontextualize on an existing dataset with ambiguous entity references. dataset we use the ambiguous biographies dataset introduced in chiang and yi @xcite which comprises biographies generated by llms for multiple entities that share similar names, such as dick hanley (swimmer) and dick hanley (footballer). in this dataset we represent the biographies generated by the llms as r and c i correspond to atomic claims generated using the methodology outlined in @xcite . for this setting, we define each claim to have a subject s i , which is ambiguous due to the nature of the dataset. the dataset provides a set of evidence documents sourced from wikipedia page of the subject disambiguation, d @xmath0,2 , d i,2 , . . .} for subjects sharing similar names as s i . this dataset is suitable for evaluating decontextuality as it consists of two properties: (i) atomic claims that require decontextualization (such as entity specification, noun completion), (ii) multiple entities with the same name that require additional disambiguation such as specifying location, occupation, or time-period. our goal is to verify the claims with the set of documents using check(). we randomly sample 726 claims from the human-annotated set for this study which belong to either supported or not_supported categories. for each claim we construct a revision using the methods and baselines baseline minimal ↑ non-minimal↓ ambig.↓ simple 16.0% 56.0% 28.0% safe 24.0% 0.0% 76.0% molecular 52.0% 24.0% 24.0% and (2) whether it is supported by the correct evidence. for each evidence associated with the claim, we compute p i,@xmath1,k , c i ) where c i is the claim processed by the particular baseline and k represents the kth ambiguous subject related document for the claim. we consider the judgment p i,k to be correct only if the prediction of the claim matches the human label and the prediction is supported by the correct entity's evidence document. overall, we observe that molecular claims strike a balance by maintaining minimality with ambiguity removal and improving accuracy. they are significantly more minimal than simple-decontext and more performant in ambiguous generations than safe-decontext. ## related work recent research in factuality verification of llm generations advocates decomposing llm generations into atomic facts or subclaims and verifying each against retrieved evidence @xcite @xcite . end-toend pipelines for factuality verification have been proposed, involving steps such as claim extraction, revision, determining checkworthiness, evidence retrieval, and verification @xcite @xcite . these papers often evaluate on recently-released datasets of errors in generations @xcite al. (2023a prior work on decontextualization has investigated basic notions like anaphora resolution @xcite , question answering frameworks (newman et al., 2023), and extract-then-decontextualize methods for summarization @xcite . in fact verification, atomic claims are made standalone before evidence retrieval via decontextualization @xcite or claim revision @xcite . decontextualization is also used to resolve ambiguity @xcite ; @xcite ; our work shares this focus. ## conclusion we introduce molecular facts and the desiderata of decontextualization in llm fact verification. we define the criteria of decontextuality and minimality in this context. through a controlled experiment, we show that localization errors due to loss of minimality by decontextualization is sensitive to the method used. we propose a method of "molecular facts" and find that they improve fact verification precision for claims from generation about ambiguous entities. we show that molecular facts strike a balance between maintaining minimality and accuracy of fact-verification.