Comparison with INFER

The Accordance INFER search command is more configurable/powerful than the FUZZY command. It has four parameters: the length of the target text segments; the number of words in a target text segment that can be ignored, which must be less than 50% of the length of the segment; the size of a source text segment in relation to a

317 _{This command looks for four-word phrases because there are four search words in} the command.

318 _{This statement and these rules, like many of the statements about FUZZY in this} section, were determined based on the analysis of the results from experimenting with FUZZY.

target text segment (i.e. how many words longer); and the name of an open

tab/window in Accordance that displays the target text.319 The minimum number of matching words required is automatically calculated as the first parameter minus the second parameter. The maximum distance between words in the source texts is the first parameter plus the third parameter. Only the first parameter needs to be stated; the second and third parameters default to zero if they are not specified (as would be the case in the example shown in Figure 3.3.3.1, below). A ‘+’ sign can be also be added to allow the matching words to appear in any order. In addition, the command can be configured to find matches based on either exact words or words that have the same lemma (or a key, if the text is a translation).320

The INFER command links the verses in two different tabs (or windows) in Accordance but only highlights the matching words in tab where the command is entered. The command can be invoked from a command line, as per Figure 3.3.3.1 below, or via a pop-up window, as per Figure 3.3.3.2 below.321

Figure 3.3.3.1 – Using INFER via a Command Line

319 _{‘The Accordance INFER Command’, Online:}

http://accordancefiles2.com/helpfiles/OSX12/Default.htm#topics/06_braa/infer_6.htm .

320 _{‘The Accordance INFER Command’.}

321 _{Both of these figures are copied from the Accordance online help page for INFER,} see ‘The Accordance INFER Command’.

Figure 3.3.3.2 – Using INFER via a Pop-up Window

As an example of how INFER might have been used in this study, or other Biblical studies, a restricted set of verses (e.g. Titus 3:5-6) would be selected in one tab (e.g. NA28), then in a second tab that displays the source texts (e.g. all the verses of the Septuagint), a command like [INFER 6, 2, 4+ NA28] would be entered (either by typing it into the command line or by automatically generating the command via the pop-up window).

This sample command would begin by splitting the target text (e.g. Titus 3:5-6) into overlapping segments of six words and then look for combinations of four or more words from a target segment that are found together in any order in a ten-word segment of the source texts.322

The INFER command is relatively easy-to-use because it automates many of the steps that are performed manually in the new method and with programs like Tracer. However, this ease-of-use comes at the cost of limiting the amount of configuration that is possible. For example, the segmentation step with INFER is simplified to dividing the texts into sequences of a fixed length, rather than allowing a user to segment based on whole sentences or clauses. There is also no apparent selection step,

322 _{This statement, like many of the statements about INFER in this section, was} determined based on the analysis of the results from experimenting with INFER.

meaning that all words, including articles and conjunctions etc., are counted in word matches. Furthermore, in the pre-processing step, the lexical alternatives can only be the words that are based on the same lemma (or the same ‘key’ in a translation); they cannot be synonyms, or words from a different language.323

However, the most significant limitations with INFER are within the featuring and scoring steps. These limitations are explained in detail in the following two

subsections. After this, an easy-to-use search command called ECHOES is suggested, which is similar to the new method that was developed for this study.

3.3.3.1 Featuring with INFER

As was noted in the survey of DH projects in Chapter 2, those projects sought to be as effective as a set of scholars in their field of research by attempting to detect a set of known parallels. Within this study, the new method follows the same process by seeking to detect all the parallels in three baseline lists: the UBS5_{, the NA}28 _and Evans’ collated list of parallels.324 _{It was noted in Chapter 1, Section 1.5.2, that some} of these known parallels for the Pastoral Epistles have only one or two matching words. Furthermore, the matching words are often separated by several intervening words in either the source or target texts. Therefore, in order to simulate the scholars of the Pastoral Epistles, this study defined a variety of reference forms (see Chapter 1, Section 1.3). These reference forms were then implemented as search features within the featuring step of the new method (see Section 3.2.4, above).

Chapters 4–7 contain an evaluation of the effectiveness of the initial set of five search features. During this evaluation/testing phase, additional search features are defined that would enable the method to detect all of the interpretable parallels in the three baseline lists.325 The method is able to add a variety of search features because it uses

323 _{Unlike in the new method used by this study, the source and target texts must be in} the same language.

324 _{Aland et al., Greek New Testament; Aland et al., Novum Testamentum Graece;} Evans, Ancient Texts.

325 _{The thematically coherent parallels that are not detected by the final set of search} features have at most one matching word. These parallels are discussed in the following chapters.

combinations of Accordance’s highly flexible ‘<within N words>’ and ‘<followed by>’ search commands.

In contrast, the INFER command is not as flexible as the method due to its requirement that ‘less that 50%’ of the target segment can be ignored.326 This limitation means that the number of matching words must be more than half of the target segment. As a consequence, the INFER command is not effective for parallels where there are only two or three matching words that are not close together.

For example, the parallel to Joel 3:1 (MT Joel 2:28) in Titus 3:5-6 is noted in the three baseline lists (UBS5, NA28 and Evans), as well as by Hübner,327 Knight,328 and

Towner.329 However, this parallel has only two matching words that are separated by two intervening words, as shown below:

οὐκ ἐξ ἔργων τῶν ἐν δικαιοσύνῃ ἃ ἐποιήσαµεν ἡµεῖς ἀλλὰ κατὰ τὸ αὐτοῦ ἔλεος ἔσωσεν ἡµᾶς διὰ λουτροῦ παλιγγενεσίας καὶ ἀνακαινώσεως πνεύµατος ἁγίου, οὗ ἐξέχεεν ἐφ᾿ ἡµᾶς πλουσίως διὰ Ἰησοῦ Χριστοῦ τοῦ σωτῆρος ἡµῶν.330 (Titus 3:5-6) Καὶ ἔσται µετὰ ταῦτα καὶ ἐκχεῶ ἀπὸ τοῦ πνεύµατός µου ἐπὶ πᾶσαν σάρκα, καὶ προφητεύσουσιν οἱ υἱοὶ ὑµῶν καὶ αἱ θυγατέρες ὑµῶν, καὶ οἱ πρεσβύτεροι ὑµῶν ἐνύπνια ἐνυπνιασθήσονται, καὶ οἱ νεανίσκοι ὑµῶν ὁράσεις ὄψονται· καὶ ἐπὶ τοὺς δούλους καὶ ἐπὶ τὰς

326 _{‘The Accordance INFER Command’.}

327 _{Hübner, Vetus Testamentum in Novo: Band 2 Corpus Paulinum, 656.}

328 _{George W. Knight III, The Pastoral Epistles (ed. I. Howard Marshall and W. Ward} Gasque; William. B. Eerdmans Publishing Company, 1999), 344.

329 _{Philip H. Towner, The Letters to Timothy and Titus (Wm. B. Eerdmans Publishing} Co., 2006), 784.

330 _{ET: ‘Not according to works of righteousness that we have done, but according to} his mercy, he saved us, through the washing of regeneration and rebirth of the Holy Spirit, whom he poured out upon us richly through Jesus Christ our savior.’

δούλας ἐν ταῖς ἡµέραις ἐκείναις ἐκχεῶ ἀπὸ τοῦ πνεύµατός µου.331 (Joel 3:1-2; MT Joel 2:28-29)

This parallel cannot be detected with a command like [INFER 4, 2 NA28] because the parameters violate one of the rules of INFER (i.e. that the number of missing words, or holes, must be ‘less than 50%’ of the target segment). Extending the size of the target segment in order to satisfy this rule, such as with the command [INFER 5, 2 NA28], would require the parallel to have three matching words. However, none of the adjacent words in the segment of the target text is in the immediate context of the source text. Extending the size of the source text segments to be quite large, for example [INFER 5, 2, 100+ NA28], would probably find three words from the target text segment within a large segment of the source text. However, such a measure would seem to be forced, since it is really only two words, πνεῦµα and ἐκχέω, that belong to the parallel.

Extending the size of the source text segments this way would also identify numerous extra verses. Since all of these verses then need to be manually inspected, this makes the whole process extremely inefficient (i.e. labor-intensive). This problem is

explained further in the following section.

3.3.3.2 Linking and Scoring with INFER

Several of the DH projects that were surveying in Chapter 2, including Tracer and Tesserae, contain a step called ‘linking’ that identifies a set of parallels by linking the source and target texts based on shared search features.332 This is then followed by a separate step called ‘scoring’ that identifies the ‘most-likely’, or highest scoring, parallels.333 The simplest way of scoring a parallel is to count the number of matching words. The most recent version of Tesserae gives a value to each individual matching word based on its own rarity, then sums these values to produce a total score for the

331 _{ET: ‘And afterward, I will pour out my Spirit on all flesh. Your sons and daughters} will prophesy, your old men will dream dreams, your young men will see visions. Even on my male servants and female servants, I will pour out my Spirit in those days.’

332 _{Franzini et al., ‘TRACER: A User Manual’; ‘Tesserae: Advanced Search’.} 333 _{Franzini et al., ‘TRACER: A User Manual’; ‘Tesserae: Advanced Search’.}

parallel.334 These DH projects then sort the parallels from the highest score down to the lowest, thereby allowing researchers to select what might seem to be the ‘most- likely’ parallels for manual analysis as potential references.

In the method proposed by this present study, the linking and scoring steps are combined in order to make the search process more efficient (see Section 3.2.5). The score that is assigned to each parallel is calculated as ‘the number of source texts that the combination of matching words appears in.’ Subsequently, the method only highlights parallels that are less than or equal to a certain score, as defined by the ‘Singular Potential’ criterion. Within the testing of the method in this study, this value was set to nine source texts. Other studies might experiment with different values. Like the new method, the INFER command combines the linking and scoring steps. The linking step, or the underlying searches of Accordance’s databases, is governed by the parameters of the command. The combinations of words that are used in its searches, as well as the allowable distance between the words in the source text, are automatically calculated based on the specified length of the segments and the number of words that can be ignored. After executing all the individual searches of the various word combinations, the results of all the searches are then displayed together in the tab where the command was entered.

For example, if Titus 3:6 (οὗ ἐξέχεεν ἐφ᾿ ἡµᾶς πλουσίως διὰ Ἰησοῦ Χριστοῦ τοῦ σωτῆρος ἡµῶν) was displayed in a tab called NA28, and the command [INFER 4, 1, 2+ NA28] was entered into another tab displaying the Septuagint, then Accordance would begin by automatically segmenting the eleven words in Titus 3:6 into eight overlapping four-word segments. The linking step (or its equivalent) would involve Accordance searching its database for all places where three words in a target

segment (i.e. 4 – 1) occur within six words (i.e. 4 + 2) of each other in the Septuagint. The tab where the command was entered would then display the combined results, which in this example is a total of 14,452 verses of the Septuagint.

Although this might appear to be very productive in that it finds many parallels, it is not efficient because it displays many parallels that are not thematically coherent with Titus 3:6. All 14,452 verses of the Septuagint would need to be manually inspected in

order to determine if they were thematically coherent. In order to put this manual workload into perspective, this study only manually inspected 1,157 verses for the whole of Titus 3 because the method only highlighted verses where the word combinations are rare, or have singular potential. Consequently, the method is more efficient than INFER because it can find parallels with low verbal similarity without generating large numbers of verses to manually inspect. This efficiency allows the new method to look for a wider variety of reference forms, making it well suited for a study of the Pastoral Epistles (and probably other target texts as well).

With the INFER command, the only way to limit the number of verses that need to be manually inspected is to modify the parameters of the command. Reducing the third parameter, the number of extra words that can be added to a source segment, will reduce the number of verses.335 _{However, this is only because it is limiting the} reference forms by requiring the words in the source text to be closer together. Increasing the first parameter, the length of the target text segment, or reducing the second parameter, the number of words of the target text segment that can be ignored, will also reduce the number of verses to be inspected.336 This is because both of these measures increase the number of matching words that are required for each parallel. However, this is effectively scoring the results based on verbal similarity.

For example, if the above command, [INFER 4, 1, 2+ NA28], was changed to either [INFER 5, 1, 2+ NA28] or [INFER 4, 0, 2+ NA28], then Accordance would only highlight verses that contain four words (i.e. 5 – 1, or 4 – 0), rather than just three (i.e. 4 – 1). As such, the results for these alternative parameters are 22 verses and 6 verses respectively, which is far more manageable then the original 14,452 verses. But in order to do this, parallels that only have three or less words are excluded. Therefore, the INFER command cannot be used to effectively and efficiently detect verbal parallels with low verbal similarity, like the ones in the three baseline lists for the Pastoral Epistles.

The main advantage of INFER is that it automatically segments the target text and then generates and executes the searches, thereby making it easy-to-use. With this

335 _{‘The Accordance INFER Command’.} 336 _{‘The Accordance INFER Command’.}

benefit in mind, the following section suggests a new easy-to-use Accordance command that would use the same search features as this study and score the results based on the rarity of the word combinations.